The Mouton Atlas of Languages and Cultures: Volume 1 The Mouton Atlas of Languages and Cultures, 1 9783110367416, 9783110373073

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Table of contents :
Preface
Contributors
Funding and support
Abbreviations
Orthographic conventions for Caucasian languages
Overview of conventions
Overview of tables
Overview of figures
Overview of maps
Overview of appendices
Contents
1. Introduction
2. Theoretical backdrop: words, things, and humans in their environment
3. Language: classification, reconstruction, and principles of change
4. Description of the database Diachronic Atlas of Comparative Linguistics
5. Atlas: Grammar
6. Atlas: Lexicon
7. Concluding chapter: an integrated view of the linguistic and cultural histories of Eurasia
Literature
Appendix 1: Languages of the current atlas
Appendix 2a: Grammar: Features, complete list (from DiACL)
Appendix 2b: Grammar: State combinations
Appendix 2c: Grammar: State combinations in languages
Appendix 2d: Grammar: Solutions 1–10 by Structure
Appendix 3a: Lexicon: list of concepts, coverage by family
Appendix 3b: Lexical data
Appendix 3c: Lexical data: statistics
Appendix 3d: Lexicon: Source language data, flow map
Appendix 4a: Language consultants
Appendix 4b: Literary sources
Appendix 4c: Geographical sources
Map Credits
Index
Recommend Papers

The Mouton Atlas of Languages and Cultures: Volume 1 The Mouton Atlas of Languages and Cultures, 1
 9783110367416, 9783110373073

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Gerd Carling (Ed.) Mouton Atlas of Languages and Cultures

Mouton Atlas of Languages and Cultures Vol 1. Europe and West, Central, and South Asia Edited by Gerd Carling

ISBN 978-3-11-037307-3 e-ISBN (PDF) 978-3-11-036741-6 e-ISBN (EPUB) 978-3-11-039333-0 Library of Congress Control Number: 2019908169 Bibliographic information published by the Deutsche Nationalbibliothek The Deutsche Nationalbibliothek lists this publication in the Deutsche Nationalbibliografie; detailed bibliographic data are available in the Internet at http://dnb.dnb.de. © 2019 Walter De Gruyter GmbH, Berlin/Boston Cover image: NikiLitov / iStock / Getty Images Typsetting: Meta Systems Publishing & Printservices GmbH, Wustermark Printing and Binding: CPI books GmbH, Leck www.degruyter.com

Preface The current project – a complete edition of the grammatical and lexical data of the database DiACL (Diachronic Atlas of Comparative Linguistics), in the form of an atlas – was launched in 2013, during a conversation with Birgit Sievert at Mouton DeGruyter during the conference ICLC 12 in Edmonton, Canada. Since then, numerous people have been involved in the compilation, contribution, checking, analyzing, and visualization of the data. Several people have contributed by solutions, ideas, conclusions, methods, models, and proposals for research questions and hypotheses. Several people ought to be mentioned here. First, I would like to thank my family for their endurance and support: my husband Tomas, my son Herman, my parents and in particular my father Hans, who unfortunately passed away during the phase of completing the manuscript. During the process, we have had many fruitful discussions on the content of this book. Further, I wish to thank, above all, Sandra Cronhamn, Astrid Zimmermann, Elnur Aliyev, Karina Vamling, Niklas Johansson, and Rob Farren, who worked very hard, day and night, weekends and holidays, in the final phase before the initial submission of the manuscript. For the resubmissions of the manuscript, I wish to thank Chundra Cathcart, Harald Hammarström, Astrid Zimmermann, Johan Frid, Sandra Cronhamn, Olof Lundgren, Ante Petrović and Victor Bogren Svensson, whose efforts enabled an extension of the content to meet the demands of the reviewers. I wish to acknowledge the anonymous reviewers for their suggestions. I also wish to thank all of the caucasologists who have contributed with their knowledge and data; in particular Merab Chukhua, who shared his etymological material with us, but also Acherdan Abregov, Teimuraz Gvatseladze, Leila Avidzba, Madzhid Khalilov, Tamar Lomadze, Revaz Tchantouria, Maka Tetradze, and Larisa Tuptsokova. I wish to thank the contributors that have been working with compiling, contributing and checking of data in various phases of the project: Anne Goergens, Josien Greidanus, Filip Larsson, Kajsa Söderqvist, and Anastasia Karlsson. I thank Ola Wikander for his valuable contribution with ancient Semitic languages, Arthur Holmer for sharing his knowledge on a number of languages, including the tricky Basque language, and Marit Julien for helping us with North Saami. I thank Erich Round, Chundra Cathcart, Harald Hammarström, and Johan Frid for crucial input on methods and models and contributions with statistical and evolutionary analyses. I am also grateful to everyone involved in solving technical issues connected to programming and statistics: first of all Rob Verhoeven, our main programmer and database designer, as well as Johan Åhlfeldt, Edin Kukovic, Johan Dahl, people at Lund University GIS Centre, in particular Karin Larsson, people at the Library of the Centre for Languages and Literature, in particular AnnSofi Gren, and Johan Frid and Mikael Novén at the Department of Linguistics, Lund University. I wish to acknowledge Václav Blažek for sharing with us his manuscript drafts with valuable data. I thank Briana Van Epps for proofreading the English text. We decided in an early phase of the production of this book to postpone the South American data, which was very important in the initial phase of our project. However, I want to acknowledge our South American colleagues for ideas and inspiration when it comes to model and method, including Chris Sinha, Vera da Silva Sinha, Ana Suelly Arruda Câmara Cabral, Alf Hornborg, and Love Eriksen. Finally, I would like to acknowledge my former supervisors, Folke Josephson and in particular Georges-Jean Pinault, who has contributed with a number of ideas and solutions in the manuscript. That said, I want to emphazise that the responsibility for any mistake, be it a misspelling, a misinterpreted etymology, or incorrect geographical information, remains entirely my own. Further, any theoretical proposals and suggestions for evaluations are entirely on my account. Lund, July 11, 2019, Gerd Carling https://doi.org/10.1515/9783110367416-202

Contributors Carling

Gerd

Writing of text (all), project leading and coordination, theoretical and methodological design (all), database and data set design (all), control and coordination of data compilation and checking (all), data checking (all), linguistic examples (Indo-European), GIS − polygon production and checking (all), checking of coding of lexical meanings for maps/statistics (all), basic statistics (all), production of figures (drawings)

Abregov Aliyev

Acherdan Elnur

Avidzba Cathcart

Leila Chundra

Chukhua Cronhamn

Merab Sandra

Farren Frid Goergens Greidanus Gvantszeladze Hammarström

Robert Johan Anne Josien Teimuraz Harald

Holmer

Arthur

Johansson

Niklas

Khalilov Kuckovic Larsson

Madzhid Edin Filip

Larsson Lomadze Novén Petrović Round

Karin Tamar Mikael Ante Erich

Söderqvist Tchantouria Tetradze Tuptsokova Vamling

Kajsa Revaz Maka Larisa Karina

Van Epps Verhoeven

Briana Rob

Wikander Zimmermann

Ola Astrid

Data contribution (Caucasian lexical) Data compilation and checking (Caucasian and Turkic lexical/grammatical, Caucasian etymological), data contribution (Caucasian and Turkic lexical) Data contribution (Caucasian lexical) Data extraction and coding (appendix 2b–2c), data checking, evolutionary model, contribution to text (ch. 5.7.2) Data contribution and checking (Caucasian lexical/etymological) Data compilation and checking (Uralic lexical/grammatical/etymological, Caucasian lexical, Indo-European lexical/grammatical, Turkic lexical), project coordination, contribution to theoretical and methodological design, control of database feeding and dataset consistency, edition of lexical meanings for meaning change charts, coding of lexical meanings for statistics/maps Data compilation and checking (Indo-European lexical/etymological) Data coding and programming, statistics (ch. 6, appendix 3c) Data compilation and checking (Indo-European/grammatical) GIS − polygon production (Europe) Data contribution and checking (Caucasian lexical) Data extraction, evolutionary model, statistical analysis, and contribution to text (ch. 6.3.7) Data compilation and checking (Basque lexical/grammatical, European lgs. grammatical), linguistic examples (Basque, Scottish Gaelic, Romanian, Bulgarian etc.), contribution to data set design (grammatical) Data compilation and checking (Indo-European lexical/grammatical), project coordination, contribution to theoretical and methodological design, production of meaning change charts (ch. 6) Data contribution (Caucasian lexical) Programming, database Data compilation and checking (Indo-European lexical/grammatical, Turkic grammatical) Design of GIS-projections, GIS − polygon design Data compilation and checking (Caucasian lexical) Preparation of statistical graphs, ch. 6 Data checking (Indo-European) Data checking (all, grammatical), statistical analysis (ch. 5.7, appendix 2d), contribution to text (ch. 5.7) Edition of lexical meanings for meaning change charts (ch. 6) Data contribution and checking (Caucasian lexical/grammatical) Data compilation, contribution, and checking (Caucasian lexical/grammatical) Data contribution (Caucasian lexical) Text feedback, linguistic examples (Caucasian), control of data compilation and checking (Caucasian lexical/grammatical), data checking (Caucasian, Russian, and Ossetian lexical/grammatical), polygon checking (Caucasian, Russian) English proof-reading Database, back-end and front-end design and implementation, data migration, data extraction and conversion Data contribution and checking (Ugaritic, Old Testament Hebrew lexical) Design of GIS-projections, GIS − polygon design, production of maps

https://doi.org/10.1515/9783110367416-203

Funding and support Agency

Project/Nr.

Period

Funding type

Contribution

Marcus and Amalia Wallenberg Foundation

LUNDIC MAW 2012.0095

2013–2016

Research Grant

Data, research, infrastructure, workshops, meetings

Marcus and Amalia Wallenberg Foundation

CHRONOS MAW 2017.0050

2018–2022

Research grant

GIS, additional research

Crafoord Foundation

20120794

2012–2013

Research Grant

Infrastructure, research (all)

Crafoord Foundation

20171050

2017–2018

Research Grant

Data, research (Caucasian)

Elisabeth Rausing Foundation

2013–2017

Travel Grants

Workshops, meetings

Uno Otterstedt Foundation

2013–2017

Travel Grants

Workshops, meetings

Faculty of Humanities and Theology, Lund University

2016–

Infrastructure support

Infrastructure

SWE-CLARIN

2016–

Infrastructure support

Infrastructure, coding, statistics

Bank of Sweden Tercentenary Foundation

2016–2017

Infrastructure support

Infrastructure

Funding for the publication has been granted by the Roy and Maj Franzén Foundation.

https://doi.org/10.1515/9783110367416-204

Abbreviations Language abbreviations Abaz Abkh Ady Agh Akk Alb Andi AngRo AnNo Arab Arm Ash Ass Ass Av Avar Azb

Abaza Abkhaz Adyghe Aghul Akkadian Albanian (Tosk) Andi Angloromani Anglo-Norman Arabic Armenian Ashkun Assamese Assyrian Avestan Avar Azerbaijani

Bal Basq Bat Ben BeRu Bes Bhi BHS Bre Bryth BSl Bud Bul

Baluchi Basque Batsbi Bengali Belorussian Beshta Bhili Buddhist Hybrid Sanskrit Breton Brythonic Balto-Slavic (branch) Budukh Bulgarian

Cat CBalt CCelt CCirc CeItIb CFin CFU Chech CIE CIIr Cir ClArm ClGr Co CoSl Cr CRom CrTat Cscand CSem CSl CT CTk Cz

Catalan Common Baltic Common Celtic Common Circassian Celtiberian Common Finnic Common Finno-Ugric Chechen Common Indo-European Common Indo-Iranian Common Iranian Classical Armenian Classical Greek Cornish Common Slavic Croatian Common Romance Crimean Tatar Common Scandinavian Common Semitic Common Slavic Common Tocharian Common Turkic Czech

https://doi.org/10.1515/9783110367416-205

Da Dar Du

Danish Dargwa Dutch

EBasq Elfd Eng Est Etr

Basque (East) Elfdalian English Estonian Etruscan

Far Finn Fr Fri Friu

Faroese Finnish French Frisian Friulian

Gag Gau Geo Ger Gil Gm Goth Guj

Gagauz Gaulish Georgian German Gilaki Germanic (branch) Gothic Gujarati

Hatt Hin Hitt Hun Hurr

Hattic Hindi Hittite Hungarian Hurrian

Ice IE IIr Ing Ir It

Icelandic Indo-European (family) Indo-Iranian (branch) Ingush Irish Italian

Ka Kab KarB Kartv Kat Kaz Khi Kho Khot Khw Kon Kryz KuKur Kum Kumy KuSor

Kashmiri Kabardian Karachay-Balkar Kartvelian (family) Kati Kazakh Khinalug Khowar Khotanese Khwarshi Konkani Kryz Kurdish (Kurmanji) Kumauni Kumyk Kurdish (Sorani)

x

Abbreviations

Lad Lah Lak Lat Latv Laz Lez LG Lith LLat Luw Lyc Lyd

Ladin Lahnda Lak Latin Latvian Laz Lezgian Low German Lithuanian Late Latin Luwian Lycian Lydian

Mai Mald Manx Mar Marw MedLat Mess Mgr MHG MiBre MiCo MiDu MiEng MiFr MiGr MiIr MiWel MLat MLG MoArm MoGr MPer

Maithili Maldivian Manx Marathi Marwari Medieval Latin Messapian Megrelian Middle High German Middle Breton Middle Cornish Middle Dutch Middle English Middle French Middle Greek Middle Irish Middle Welsh Medieval Latin Middle Low German Modern Armenian Modern Greek Middle Persian

Nep Norw NorwB NorwN NoSa

Nepali Norwegian Norwegian (Bokmål) Norwegian (Nynorsk) Northern Saami

OAw OBre OCat Occ OChin OCo OCS OCz ODan ODu OGut OE OFr OFran OFri OGeo OGuj OHG

Old Awadhi Old Breton Old Catalan Occitan Old Chinese Old Cornish Old Church Slavonic Old Czech Old Danish Old Dutch Old Gutnish Old English Old French Old Franconian Old Frisian Old Georgian Old Gujarati Old High German

OIr OIt OMar ON OPer OPol OPor OPro OPru OR ORu OS Osc OSp Oss OSw OTHeb OTk OWel

Old Irish Old Italian Old Marathi Old Norse Old Persian Old Polish Old Portuguese Old Provençal Old Prussian Oriya Old Russian Old Saxon Oscan Old Spanish Ossetian (Iron) Old Swedish Old Testament Hebrew Old Turkic Old Welsh

Pa PAAs PAlb Par PArm Pas PBalt PBryth PBSl PCelt PGalRom PD Per PFi PFU PGm Phoe Phr PIAr PIbRom PIE PIIr PIr PItal Pkt PKv PN PNGm PNWC Pol Por Pras Pro PRom PSl PSSl PT PU Pu PZ

Pali Proto-Afro-Asiatic Proto-Albanian Parachi Proto-Armenian Pashto Proto-Baltic Proto-Brythonic Proto-Balto-Slavic Proto-Celtic Proto-Gallo-Romance Proto-Dagestanian Persian Proto-Finnic Proto-Finno-Ugric Proto-Germanic Phoenician Phrygian Proto-Indo-Aryan Proto-Ibero-Romance Proto-Indo-European Proto-Indo-Iranian Proto-Iranian Proto-Italic Prakrit Proto-Kartvelian Proto-Nakh Proto-North-Germanic Proto-Northwest Caucasian Polish Portuguese Prasun Provençal Proto-Romance Proto-Slavic Proto-South-Slavic Proto-Tocharian Proto-Uralic Punjabi Proto-Zan

Language abbreviations

Raj RoAr RoBGur RoBu RoBur RoCr RoDol RoEr RoESl RoGu RoGur RoHuV RoKa RoKel RoKoA RoLat RoLith RoLov Rom Roma RoMaA RoMDj RoNR RoPr RoRo RoSe RoSGu RoSi RoUr RoVe RoWe Ru Rut

Rajasthani Romani (Arli) Romani (Banatiski Gurbet) Romani (Bugurdži) Romani (Burgenland) Romani (Crimean) Romani (Dolenjski) Romani (Sofia Erli) Romani (East Slovak) Romani (Gurvari) Romani (Gurbet) Romani (Hungarian Vend) Romani (Kale) Romani (Kelderash) Romani (Kosovo Arli) Romani (Latvian) Romani (Lithuanian) Romani (Lovara) Romanian Romansh Romani (Macedonian Arli) Romani (Macedonian Džambazi) Romani (North Russian) Romani (Prekmurski) Romani (Romungro) Romani (Sepečides) Romani (Sremski Gurbet) Romani (Sinte) Romani (Ursari) Romani (Veršend) Romani (Welsh) Russian Rutul

SAlt Sard ScGae SCr ScRo Scy Sem Ser Shug Sic Sin

Southern Altai Sardinian Scottish Gaelic Serbo-Croatian Scandoromani Scythian Semitic (family) Serbian Shughni Sicilian Sindhi

Sinh Skt Slo Slovak Sog Sp StAr Sw Sva SwGer Syr

Sinhalese Sanskrit Slovene Slovakian Sogdian Spanish Standard Arabic Swedish Svan Swiss German Syriac

TA Tab Taj Tal TB Thr Tre Tsakh Tur Turk Turkm Tuv

Tocharian A Tabasaran Tajik Talysh Tocharian B Thracian Tregami Tsakhur Turkish Turkic (family) Turkmen Tuvan

Uby Udi Ugar Ukr Umbr Ur USorb Uygh Uzb

Ubykh Udi Ugaritic Ukrainian Umbrian Urdu Upper Sorbian Uyghur Uzbek

VulL

Vulgar Latin

Wai Wak Wall WBasq Wel

Waigali Wakhi Walloon Basque (West) Welsh

Yag Yi

Yagnobi Yiddish

xi

xii

Abbreviations

Grammar abbreviations (listed glossings target grammatical categories not fund in Leipzig glossing rules)

a abl. abs. acc. AD adj all. ALLOC anim. c com. dat. erg. f gen. infl instr. loc. m MPASS n nom. nt. obl. perl. pl pl. ppart s sg sg. vn voc.

alternans (gender) ablative absolutive accusative adessive adjective allative allocutive agreement animated common gender comitative dative ergative feminine genitive inflected form instrumental locative masculine middle-passive neuter nominative neuter oblique perlative plural plural preterite participle substantive singular singular verbal noun vocative

(appendix)

(glossing) (appendix) (glossing) (appendix)

(appendix) (appendix)

(appendix) (glossing) (appendix)

(appendix) (appendix) (appendix) (appendix) (appendix)

Other abbreviations and symbols

Other abbreviations and symbols < ← b. c. coll. comp. der. dim. esp. etym. f. gen. l. lit. m. migr. orig. pl. ref. s. sing. spe. sth. substr. symb. uct. w. y.

derived from, inherited from borrowed from big certain collective compound derivation diminutive especially etymology female generic large literary male migration word originally plural reference small singular specific something substrate sound symbolic uncertain wild young

xiii

https://doi.org/10.1515/9783110367416-206

Vibrant

Approximant

Lateral approximant

Lateral fricative

Lateral affricate

Fricative (Spirants)

Affricate

f:

t’

s

f f’

voiceless

glottalized

ḷ‘

glottalized

r

l

l‘

voiceless ḷ‘:

l‘:

glottalized ˜l

ˇḷ:

ˇḷ

voiced

ˇl:

L ˇl

aspirated

s:

c’:

cʰ:

t’:

tʰ:

intensive

voiced

s’

z

c’ v

glottalized

voiced

c cʰ

preruptive

aspirated

w

p’:



t

ʒ

p’

glottalized

pʰ:

d

n

normal

Alveolar

voiced

p



preruptive

b

Plosive

aspirated

m

voiced

Nasal

intensive

normal

normal

intensive

Labio-Dental

Labial





t’ʲ

tʰʲ





palatalized

š’

š

ž

č’

čʰ

č

ǯ

normal

š:

č’:

čʰ:

intensive

Post-Alveolar

Orthographic conventions for Caucasian languages

šʲ

žʲ

č’ʲ

čʰʲ

č

ǯʲ

palatalized

j

ś

ź

ć’

ć

ʒˊ

Palatal

χ

ɣ

k’



k

g

normal

Velar

k’:

kʰ:

intensive

ɣʲ

palatalized

x

ʁ

q’



q

ɢ

normal

Uvular

x:

q’:

qʰ:

intensive



palatalized

Ɂ

ħ

ω



Paryn- Glotgeal talized

h

Laryngael

Front

close

Central Unrounded

Back Rounded

Unrounded

Suprasegmentals

Unrounded

Rounded

Rounded

i

ü

u

Simple

ü:

u:

Long

ĭ

ŭ

Short





Pharyngeal

ĩ

ũ

Nasal

í mid

e

Stressed ö

o

Simple

e:

o:

Long

ĕ

ŏ

Short



Pharyngeal

õ

Nasal



ə

ə.

ẽ é open

ə′

Stressed

æ

a

Simple

æ:

a:

Long

ă

Short



Pharyngeal

ã

Nasal

á

Stressed

PROCESSES . pharyngealization ʲ palatalization ʷ labialization ~ nasalization : intensive consonants ˳ ˳ dent-labialization • strong consonants

Overview of conventions General categories of grammar in discussions in text are marked by initial lower-case letter, e.g., alignment, case, nominative. Categories representing grammar features of the database are referred to by initial upper-case letter, Alignment, Case, Simple past. UPPER-CASE letters are used for defining grammar feature acronyms in the database, e.g., OBL, DAT, GEN, or classes of concepts in lexical data, e.g., ACTIVITIES. Small caps are used in glossings in examples, e.g., prs, dat, and for general meanings (i.e., not meanings in individual languages), e.g., bull, to strike, wolf, predator.

https://doi.org/10.1515/9783110367416-207

Overview of tables No.

Caption

Table 1

Overview of domains and features of the dataset used in this atlas (for a complete list of in the database DiACL, including questionnaire and ID, see appendix 2a)

Table 2

Number and type of languages with grammar data in this volume

Table 3

Basic type correlations for alignment systems and evaluation of the outcome

Table 4

Model for coding of basic alignment types against word class and tense

Table 5

List of features of the grid Alignment (appendix 2a)

Table 6

Samples of state combinations (i.e., existing combinations of 1/0, see 5.1.1) for the alignment feature Noun: Present Progressive (see maps 3a–c)

Table 7

Grid Nominal morphology: features, occurring variants (V), attested combinations of 1 and 0 (C), and explanation

Table 8

Overview of variants of the feature Nominal morphology / Nominal case (note that the order of variants is alphabetical), with reference to example and ID (appendix 2a)

Table 9

Sample of state combinations for the feature Nominal morphology / Nominal case in Swedish, Classical Greek, Tocharian A, Turkish, and Romani (Sinte) (for a complete list of coding patterns see appendix 2b–c)

Table 10

Variants of the feature Nominal morphology: Pronominal case with ID (appendix 2a)

Table 11

Simplified state combinations (numbered by order of frequency in the data) for the feature Nominal morphology: Nominal case (for a complete list of the underlying order of variants and the combinations of 1/0, see appendix 2b)

Table 12

Simplified state combinations (numbered by order of frequency in the data) for the feature Nominal morphology: Pronominal case (for a complete list of the underlying order of variants and the combinations of 1/0, see appendix 2b)

Table 13

Variants of the feature Nominal morphology: Nominal case with examples and ID

Table 14

State combinations (numbered by order of frequency in the data) for the feature Nominal morphology: Case marking (for a complete list of the underlying order of variants and the combinations of 1/0, see appendix 2b) (for details see further appendix 2b–c)

Table 15

Variants of the feature Nominal morphology: Gender/ Noun class

Table 16

Assignment to noun classes (taking gender agreement) in Khwarshi

Table 17

State combinations (numbered by order of frequency) of the feature Nominal morphology: Gender / Noun class (for a complete list of the underlying order of variants and the combinations of 1/0, see appendix 2b)

Table 18

Variants of the feature Definiteness marking, with reference to examples and ID (appendix 2a)

Table 19

State combinations for the feature Nominal morphology: Definiteness marking (for a complete list of the underlying order of variants and the combinations of 1/0, see appendix 2b)

Table 20

Features, occurring variants (V), attested state combinations of 1 and 0 (C), and explanation, for the grid Verbal morphology

Table 21

Variants of the feature Verbal morphology: Present progressive, A (see table 20)

Table 22

Features, occurring variants (V), attested state combinations of 1 and 0 (C), and explanation, for the grid Tense

Table 23

State combinations for the feature Continuous present (for a complete list of the underlying order of variants and the combinations of 1/0, see appendix 2b) (see appendix 2c)

Table 24

Variants of the feature Future, with example and ID (appendix 2a–c)

Table 25

State combinations for the feature Future, maps 14a–c (for a complete list of the underlying order of variants and the combinations of 1/0, see appendix 2b) (see appendix 2c, maps 12a–c)

https://doi.org/10.1515/9783110367416-208

xviii

Overview of tables

(continued) No.

Caption

Table 26

Change in percentages of OV vs. VO in classical Latin. Simplification after (Danckaert 2015)

Table 27

Selected Word order coding for Latin and Old French (see also table 31)

Table 28

Word order distributions in Classical and NT Greek (Ebeling 1903; Haug 2009)

Table 29

Verbal positions in Classical Greek. After (Lühr 2015)

Table 30

Word order: features, occurring variants (V), attested combinations of 1 and 0 (C), and explanation

Table 31

Features and variants of Word order in our data

Table 32

Samples of reconstruction of multistate characters of the grammar data set (Indo-European languages only). For each multistate character, the likelihood of a set of evolutionary transition rates between each pair of states under a tree topology and observed data are computed according to Felsenstein’s Pruning Algorithm, which is used to estimate the probability of a state at the root of the tree. We use RStan to infer the posterior probabilities of these rates, marginalizing over a sample of trees. Numbers of the first column are for reference and refer to features (appendix 2a), the following set of variants (appendix 2a) represent our defined multistate characters, the column Probability gives the state probability at the root of the tree, and the column Interpretation explains the multistate character as a linguistic property. Extracted from (Carling and Cathcart Forthcoming)

Table 33a

Overview of clusters, interpreted as zones, based on full data set (note that the numbers are generated by the program and have no relevance to similarities between clusters, see fig. 6 for a tree of pairwise mutual similarities between clusters)

Table 33b

Hybrid or border zones. These zones are defined as a number of languages which are adjacent in geography and which display an admixture component from one or several groups higher than 10 %

Table 34

List of thematic groups in the atlas and their corresponding OCM Subject category number

Table 35

List of cultural concepts of the atlas with satisfactory coverage. The classification below is based on OCM standard system of cultural classification, combined with the occurrence of colexification/ meaning change of the data as well as the concepts’ behavior in terms of borrowability, semantic instability, and lexical cognacy. Note that the classification may differ slightly from the organization of chapters in the atlas in 6.4–6.12.

Table 36

Overview of semantic coding types of lexemes and their inclusion in visualizations (maps, graphs)

Table 37

Percentages of the genders common gender (c), feminine (f), masculine (m), and neuter (n) of the 6727 lexemes in the data that have a secured assigned gender (Indo-European languages only). For an overview of gender systems in our data, see map 7

Table 38

Probabilities at the ancestral node of the proto-langue (Proto-Indo-European) for the different meanings of the etymological trees of PIE *kʷel-o- ‘wheel, circle’ (79981) and PIE *Hróth₂o- ‘wheel, circle’ (80116) by means of evolutionary reconstruction, calculating gain/loss probabilities over a reference tree (from Glottolog), using a peeling algorithm (Felsenstein 2004)

Table 39

Summary of rates of borrowability, instability and cognacy, and hierarchy of gender assignment for classes (for Indo-European). The levels are estimations based on the distribution of rates of the boxplots in fig. 53–56. Gender hierarchies imply the order of frequency by genders in the Indo-European data, based on table 37. M = masculine, F = feminine, N = neuter. M > F indicates that masculine is more frequent than feminine, M/F indicates that masculine and feminine are equally frequent. The column animacy indicates whether concepts of the class are animate, as opposed to animate (for the evaluation of gender hierarchies)

Overview of figures No.

Caption

Originator

Fig. 1

Processes of language change

Gerd Carling

Fig. 2

The tree and wave models

Gerd Carling

Fig. 3

BEAST densitree, based on basic vocabulary data for Indo-European languages (from DiACL database)

Chundra Cathcart

Fig. 4

Tables and relations in the database DiACL. Different colours represent various subsections of the database. Arrows indicate relations between tables: they show the direction of links inside the infrastructure. Red: subsection language and language metadata; blue: subsection typology/morphosyntax; brown: subsection sources; green: subsection lexicon. Tables and categories are described more carefully in the text

Gerd Carling

Fig. 5

Graph illustrating the feature-hierarchical model of grammar data, used in the database. From (Carling, Larsson, et al. 2018)

Gerd Carling

Fig. 6

Structure analysis on typological data (all features, all languages), dividing into 10 clusters, including a tree diagram of pairwise mutual similarities between clusters

Erich Round

Fig. 7

Visualization of the process of computer-based ancestral state reconstruction of features, such as comparative concepts in grammar. The probability that a feature/variant is present at a given node is estimated, based on the evolutionary rates inferred for the feature/variant, as well as the probability that the feature/variant is present in descendant nodes

Chundra Cathcart

Fig. 8a

Timeline of number of gains and losses of Indo-European languages in the grammar data, using a strict clock, which allows rates to vary stochastically from branch to branch (Felsenstein 2004) and a gain-loss (probabilistic, Bayesian, MCMC, character-based) model, where the likelihood of the tree is the product of all branch likelihoods and branch likelihood equals probability of descendant state, given: a) most likely ancestral state, b) branch length, c) gain parameter, and d) loss parameter (Cathcart et al. 2018)

Chundra Cathcart

Fig. 8b

Histogram of documentation dates of languages in the grammar data

Chundra Cathcart

Fig. 9

Graph explaining the difference between the cognacy method (i.e., of lexicostatistics) and etymology method of organizing lexemes: in lexicostatistical cognacy method blue circles and orange circles belong to two different cognacies, blood versus meat, in the etymology method all circles belong to one tree

Gerd Carling

Fig. 10a

Etymological tree of the Indo-European words for bear, from the database DiACL

DiACL/ Rob Verhoeven

Fig. 10b

Etymological tree of the Caucasian words for bear, from the database DiACL

DiACL/ Rob Verhoeven

Fig. 11

Organization of Word Lists Items (lexical concepts) in the database DiACL

Gerd Carling

Fig. 12

Colexification and meaning change of the concept deer (Indo-European)

Niklas Johansson

Fig. 13

Borrowability (x), semantic instability (y) and cognacy (node size) for GAME ANIMALS

Johan Frid

Fig. 14

Borrowability (x), semantic instability (y) and cognacy (node size) for PREDATORS Johan Frid

Fig. 15a

Colexification and meaning change for PREDATORS (Indo-European)

Niklas Johansson

Fig. 15b

Colexification and meaning change for PREDATORS (Caucasian)

Niklas Johansson

Fig. 16

Borrowability (x), semantic instability (y) and cognacy (node size) for PREDATOR BIRDS

Johan Frid

Fig. 17a

Colexification and meaning change for PREDATOR BIRDS (Indo-European)

Niklas Johansson

Fig. 17b

Colexification and meaning change for PREDATOR BIRDS (Caucasian)

Niklas Johansson

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Overview of figures

(continued) No.

Caption

Originator

Fig. 18

Borrowability (x), semantic instability (y) and cognacy (node size) for DOMESTIC ANIMALS (dog, cat)

Johan Frid

Fig. 19

Borrowability (x), semantic instability (y) and cognacy (node size) for DOMESTIC INSECTS (bee)

Johan Frid

Fig. 20

Borrowability (x), semantic instability (y) and cognacy (node size) for PIG RAISING

Johan Frid

Fig. 21a

Colexification and meaning change for PIG RAISING (including wild boar) (Indo-European)

Niklas Johansson

Fig. 21b

Colexification and meaning change for PIG RAISING (including wild boar) (Caucasian)

Niklas Johansson

Fig. 22

Borrowability (x), semantic instability (y) and cognacy (node size) for CATTLE

Johan Frid

Fig. 23a

Colexification and meaning change for CATTLE (including bison) (Indo-European)

Niklas Johansson

Fig. 23a

Colexification and meaning change for CATTLE (including bison) (Caucasian)

Niklas Johansson

Fig. 24a

Colexification and meaning change for the concept milk (Indo-European)

Niklas Johansson

Fig. 24b

Colexification and meaning change for the concept milk (Caucasian)

Niklas Johansson

Fig. 25

Borrowability (x), semantic instability (y) and cognacy (node size) for SMALL CATTLE

Johan Frid

Fig. 26

Borrowability (x), semantic instability (y) and cognacy (node size) for POULTRY

Johan Frid

Fig. 27a

Colexification and meaning change for meat and grease (Indo-European)

Niklas Johansson

Fig. 27b

Colexification and meaning change for meat and grease (Caucasian)

Niklas Johansson

Fig. 28a

Colexification and meaning change for cultivated field and furrow (Indo-European)

Niklas Johansson

Fig. 28b

Colexification and meaning change for cultivated field and furrow (Caucasian)

Niklas Johansson

Fig. 29a

Colexification and meaning change for IMPLEMENTS and plow (n) (IndoEuropean)

Niklas Johansson

Fig. 29b

Colexification and meaning change for IMPLEMENTS and plow (n) (Caucasian)

Niklas Johansson

Fig. 30a

Borrowability (x), semantic instability (y) and cognacy (node size) for TILLAGE

Johan Frid

Fig. 30b

Borrowability (x), semantic instability (y) and cognacy (node size) for IMPLEMENTS

Johan Frid

Fig. 31

Borrowability (x), semantic instability (y) and cognacy (node size) for CROPS

Johan Frid

Fig. 32a

Colexification and meaning change for CROPS (Indo-European)

Niklas Johansson

Fig. 32b

Colexification and meaning change for CROPS (Caucasian)

Niklas Johansson

Fig. 33

Borrowability (x), semantic instability (y) and cognacy (node size) for VEGETABLES AND FRUIT

Johan Frid

Fig. 34a

Colexification and meaning change for apple and grape (Indo-European)

Niklas Johansson

Fig. 34b

Colexification and meaning change for apple and grape (Caucasian)

Niklas Johansson

Fig. 35

Borrowability (x), semantic instability (y) and cognacy (node size) for DRINK AND DRUGS

Johan Frid

Fig. 36a

Colexification and meaning change for wine, mead and honey (Indo-European)

Niklas Johansson

Fig. 36b

Colexification and meaning change for wine, mead and honey (Caucasian)

Niklas Johansson

Fig. 37

Borrowability (x), semantic instability (y) and cognacy (node size) for PRODUCTS

Johan Frid

Fig. 38

Borrowability (x), semantic instability (y) and cognacy (node size) for ACTIVITIES

Johan Frid

Overview of figures

xxi

(continued) No.

Caption

Originator

Fig. 39

Borrowability (x), semantic instability (y) and cognacy (node size) for MATERIALS

Johan Frid

Fig. 40a

Colexification and meaning change for fur, leather and wool (Indo-European)

Niklas Johansson

Fig. 40a

Colexification and meaning change for fur, leather and wool (Caucasian)

Niklas Johansson

Fig. 41

Borrowability (x), semantic instability (y) and cognacy (node size) for TREES

Johan Frid

Fig. 42

Borrowability (x), semantic instability (y) and cognacy (node size) for METALS

Johan Frid

Fig. 43a

Colexification and meaning change for METALS (Indo-European)

Niklas Johansson

Fig. 43b

Colexification and meaning change for METALS (Caucasian)

Niklas Johansson

Fig. 44

Borrowability (x), semantic instability (y) and cognacy (node size) for WEAPONS

Johan Frid

Fig. 45a

Colexification and meaning change for WEAPONS (Indo-European)

Niklas Johansson

Fig. 45b

Colexification and meaning change for WEAPONS (Caucasian)

Niklas Johansson

Fig. 46

Borrowability (x), semantic instability (y) and cognacy (node size) for DRAFT ANIMALS

Johan Frid

Fig. 47a

Colexification and meaning change for horse and donkey (Indo-European)

Niklas Johansson

Fig. 47b

Colexification and meaning change for horse and donkey (Caucasian)

Niklas Johansson

Fig. 48

Borrowability (x), semantic instability (y) and cognacy (node size) for VEHICLES

Johan Frid

Fig. 49a

Colexification and meaning change for VEHICLES (Indo-European)

Niklas Johansson

Fig. 49b

Colexification and meaning change for VEHICLES (Caucasian)

Niklas Johansson

Fig. 50

Borrowability (x), semantic instability (y) and cognacy (node size) for SEASONS

Johan Frid

Fig. 51a

Colexification and meaning change for SEASONS (Indo-European)

Niklas Johansson

Fig. 51b

Colexification and meaning change for SEASONS (Caucasian)

Niklas Johansson

Fig. 52

Average borrowability (x), semantic instability (y) and cognacy (node size) per class of concepts

Johan Frid

Fig. 53

Boxplot of average rates of borrowability of classes, organized from highest to lowest

Johan Frid

Fig. 54

Boxplot of average rates of semantic instability of classes, organized from highest to lowest

Johan Frid

Fig. 55

Boxplot of average rates of colexification of classes, organized from highest to lowest

Johan Frid

Fig. 56

Boxplot of average rates of cognacy of classes, organized from highest to lowest Johan Frid

Fig. 57

Schematic representation of the different cultural zones, pertaining to CULTURE and NATURE, and their most characteristic behavior in terms of lexical change

Gerd Carling

Fig. 58

The spaces of evolutionary behavior of farming vocabularies

Gerd Carling

Overview of maps No.

Caption

1

Topographic map of the macro-area covered in our data, with the particular projection used in this atlas

2a

Living languages with data in our corpus (for abbreviations see introduction, for metadata see appendix 1)

2b

Historical languages with data in our corpus (for abbreviations see introduction, for metadata see appendix 1)

2c

Romani languages with data in our corpus (for abbreviations see introduction, for metadata see appendix 1)

3a

Alignment by Nouns in Present Progressive

3b

Alignment by Nouns in Present Progressive

3c

Alignment by Nouns in Present Progressive

4a

Alignment by Nouns in Simple Past

4b

Alignment by Nouns in Simple Past

4c

Alignment by Nouns in Simple Past

5a

Alignment by Pronouns in Present Progressive

5b

Alignment by Pronouns in Present Progressive

5c

Alignment by Pronouns in Present Progressive

6a

Alignment by Pronouns in Simple Past

6b

Alignment by Pronouns in Simple Past

6c

Alignment by Pronouns in Simple Past

7a

Gender and Noun class marking

7b

Gender and Noun class marking

7c

Gender and Noun class marking

8a

Nominal case system

8b

Nominal case system

8c

Nominal case system

9a

Pronominal case system

9b

Pronominal case system

9c

Pronominal case system

10a

Realization of case marking in a Noun Phrase

10b

Realization of case marking in a Noun Phrase

10c

Realization of case marking in a Noun Phrase

11a

Definiteness marking

11b

Definiteness marking

11c

Definiteness marking

12a

Agreement with respect to Agent (A) in Present Progressive

12b

Agreement with respect to Agent (A) in Present Progressive

12c

Agreement with respect to Agent (A) in Present Progressive

13a

Agreement with respect to Agent in Simple Past

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xxiv

Overview of maps

(continued) No.

Caption

13b

Agreement with respect to Agent in Simple Past

13c

Agreement with respect to Agent in Simple Past

14a

Future tense marking

14b

Future tense marking

14c

Future tense marking

15a

Word order Adposition − Noun

15b

Word order Adposition − Noun

15c

Word order Adposition − Noun

16a

Word order Noun − Adjective

16b

Word order Noun − Adjective

16c

Word order Noun − Adjective

17a

Word order Noun – Relative clause

17b

Word order Noun – Relative clause

17c

Word order Noun – Relative clause

18a

Word order Noun – Possessor (Genitive)

18b

Word order Noun – Possessor (Genitive)

18c

Word order Noun – Possessor (Genitive)

19a

Position of Question word

19b

Position of Question word

19c

Position of Question word

20a

Word order in Main Clauses

20b

Word order in Main Clauses

20c

Word order in Main Clauses

21a

Word order Subordinate Clause

21b

Word order Subordinate Clause

21c

Word order Subordinate Clause

22a

Word order Object – Infinitive

22b

Word order Object – Infinitive

22c

Word order Object – Infinitive

23a

Word order Object − Participle

23b

Word order Object − Participle

23c

Word order Object − Participle

24a

Word order Clitic Pronoun – Finite Verb (Predicate)

24b

Word order Clitic Pronoun – Finite Verb (Predicate)

24c

Word order Clitic Pronoun – Finite Verb (Predicate)

25a

Word order Clitic Pronoun – Infinitive Verb

25b

Word order Clitic Pronoun – Infinitive Verb

25c

Word order Clitic Pronoun – Infinitive Verb

Overview of maps

(continued) No.

Caption

26a

Word order Clitic Pronoun – Participle Verb

26b

Word order Clitic Pronoun – Participle Verb

26c

Word order Clitic Pronoun – Participle Verb

27a

Pie chart map showing distribution of clusters of fig. 6 (modern languages)

27b

Pie chart map showing distribution of clusters of fig. 6 (historical languages)

27c

Pie chart map showing distribution of clusters of fig. 6 (Romani)

28a

Cognacy map for the concept wolf (modern languages)

28b

Cognacy map for the concept wolf (historical languages)

29a

Cognacy map for the concept bear (modern languages)

29b

Cognacy map for the concept bear (historical languages)

30a

Cognacy map for the concept lion (modern languages)

30b

Cognacy map for the concept lion (historical languages)

31a

Cognacy map for the concept jackal (modern languages)

31b

Cognacy map for the concept jackal (historical languages)

32a

Cognacy map for the concept dog (modern languages)

32b

Cognacy map for the concept dog (historical languages)

33a

Cognacy map for the concept cat (modern languages)

33b

Cognacy map for the concept cat (historical languages)

34a

Cognacy map for the concept bull (modern languages)

34b

Cognacy map for the concept bull (historical languages)

35a

Cognacy map for the concept milk (modern languages)

35b

Cognacy map for the concept milk (historical languages)

36a

Cognacy map for the concept sheep (modern languages)

36b

Cognacy map for the concept sheep (historical languages)

37a

Cognacy map for the concept wool (modern languages)

37b

Cognacy map for the concept wool (historical languages)

38a

Cognacy map for the concept plow (n) (modern languages)

38b

Cognacy map for the concept plow (n) (historical languages)

39a

Cognacy map for the concept grain (modern languages)

39b

Cognacy map for the concept grain (historical languages)

40a

Cognacy map for the concept wheat (modern languages)

40b

Cognacy map for the concept wheat (historical languages)

41a

Cognacy map for the concept barley (modern languages)

41b

Cognacy map for the concept barley (historical languages)

42a

Cognacy map for the concept apple (modern languages)

42b

Cognacy map for the concept apple (historical languages)

43a

Cognacy map for the concept flax (modern languages)

43b

Cognacy map for the concept flax (historical languages)

xxv

xxvi

Overview of maps

(continued) No.

Caption

44a

Cognacy map for the concept salt (modern languages)

44b

Cognacy map for the concept salt (historical languages)

45a

Cognacy map for the concept wine (modern languages)

45b

Cognacy map for the concept wine (historical languages)

46a

Cognacy map for the concept copper (modern languages)

46b

Cognacy map for the concept copper (historical languages)

47a

Cognacy map for the concept iron (modern languages)

47b

Cognacy map for the concept iron (historical languages)

48a

Cognacy map for the concept gold (modern languages)

48b

Cognacy map for the concept gold (historical languages)

49a

Cognacy map for the concept sword (modern languages)

49b

Cognacy map for the concept sword (historical languages)

50a

Cognacy map for the concept horse (modern languages)

50b

Cognacy map for the concept horse (historical languages)

51a

Cognacy map for the concept donkey (modern languages)

51b

Cognacy map for the concept donkey (historical languages)

52a

Cognacy map for the concept wheel (modern languages)

52b

Cognacy map for the concept wheel (historical languages)

53a

Cognacy map for the concept yoke (modern languages)

53b

Cognacy map for the concept yoke (historical languages)

54a

Cognacy map for the concept winter (modern languages)

54b

Cognacy map for the concept winter (historical languages)

55a

Cognacy map for the concept spring (modern languages)

55b

Cognacy map for the concept spring (historical languages)

56a

Cognacy map for the concept summer (modern languages)

56b

Cognacy map for the concept summer (historical languages)

57a

Loanword flow map, showing the position of source languages or branches/proto-languages in the data

57b

Loanword flow map, showing connections in the data between source and target languages

58

Overview of the sketched development areas, accretion zones and peripheries of the macro-area of our corpus

Overview of appendices No.

Content

1 2 2 2 2 3 3

a b c d a b

3 3 4 4 4

c d a b c

Languages and Language metadata Grammar: Typological features, list Grammar: State combinations Grammar: State combinations in languages Grammar: Language clusters Lexicon: Word List Items (all) Lexicon: Lexical Database, organized by 1) Family, 2) Concept, 3) Top node, 4) Language (alphabetically) Lexicon: Statistics, borrowability, semantic instability, and cognacy Lexicon: Borrowability flow map, source languages Data sources: Consultants Data sources: Literary Data sources: Geographic data

https://doi.org/10.1515/9783110367416-211

Contents Preface

v

Contributors

vii viii

Funding and support Abbreviations

ix

Orthographic conventions for Caucasian languages Overview of conventions Overview of tables

xvii

Overview of figures

xix

Overview of maps

xv

xxiii

Overview of appendices 1 1.1 1.2 1.3 1.4 1.5

xiv

xxvii

1.6

Introduction 1 1 Why an atlas of languages and cultures? 2 Defining our aim: observing language variation by empirical methods 4 The setting: Eurasia from the Neolithic revolution to the Industrial Age 5 Languages, language families and cultural groups in our data Language extension: policies for rendering language extension by polygons in 13 the atlas 13 Orthographic policy for languages of our corpus

2 2.1 2.2

Theoretical backdrop: words, things, and humans in their environment Sociocultural reconstruction 14 Models and methods for organizing and selecting data 15

3 3.1 3.2 3.3 3.4

Language: classification, reconstruction, and principles of change Principles of change 17 Comparative and evolutionary models of reconstruction 18 Grammar: reconstruction and principles of change 19 Lexicon: classification, reconstruction and principles of change

4 4.1 4.2 4.3 4.4 4.5 4.5.1

Description of the database Diachronic Atlas of Comparative Linguistics Background and aim 23 Rationale 23 Language areas and languages 23 Data types and design policies 24 Database structure: tables and relations 24 Language metadata: time, space and family tree topology 25

14

17

20 23

xxx

Contents

5 5.1 5.1.1 5.1.2 5.1.3 5.1.4 5.2 5.3 5.4 5.4.1 5.4.2 5.4.3 5.4.4 5.5 5.5.1 5.5.2 5.6 5.7 5.7.1 5.7.2 5.8

Atlas: Grammar 27 Grammar: feature organization and coding 27 Description of the model for organizing features 27 Grammar data set: basic principles of selection of features 28 Coding policies 29 Motivation for our selection of features 30 Grammar visualizations: aim and models 30 Alignment 31 Nominal morphology 51 Case 51 Gender and Noun class 73 Prepositional agreement 75 Definiteness 75 Verbal morphology 81 Agreement in person, number and gender 81 Tense 91 Word order 97 Analyzing the data: synchronic and diachronic models 155 Cluster analysis and geographic distribution of groups 155 A diachronic model of evolutionary reconstruction 163 Discussion: Grammar 170

6 6.1 6.1.1 6.1.2 6.1.3 6.1.4 6.1.5 6.1.6 6.2 6.2.1 6.2.2 6.3 6.3.1 6.3.2 6.3.3 6.3.4 6.3.5

Atlas: Lexicon 179 Lexicon: feature organization and coding 179 Introduction 179 Cognacy coding and etymology coding 181 Lexemes: core of the subsection Lexicology 184 Word Lists: functional hierarchies of lexical concepts 184 Organization of etymologies 185 How to deal with etymological reliability and macro-etymologies 185 Culture vocabularies: aim and definition 186 Aim of the culture vocabulary atlas 186 Motivation for selection and classification of concepts of the atlas 187 Organization, classification and visualization of lexical data 189 Organization of chapters and classification of concepts 189 Categories of lexemes and data coding principles for statistical filtering 192 Principles of maps: cognacy maps and loanword flowmap 193 Colexifying and co-cognatic meaning charts 194 Statistics: borrowability, semantic variability/instability, colexification, cognacy productivity, and gender 196 Statistics: gender 198 Evolutionary reconstruction of meaning gain and loss 201 Interim summary: Lexicon 201 Hunting and trapping 203 Introduction 203 Game animals 204 Predator animals 207 Predator birds 227 Animal husbandry 229 Domestic animals 229 Pet animals: dog and cat 230

6.3.6 6.3.7 6.3.8 6.4 6.4.1 6.4.2 6.4.3 6.4.4 6.5 6.5.1 6.5.2

xxxi

Contents

239 Domesticated insects: the honeybee 240 Pig raising 243 Bovine cattle and dairying 253 Pastoral activities: sheep and goat 259 Wool production 263 Poultry 264 Animal products 265 Agriculture 265 Introduction 267 Land use 269 Tillage 275 Cereal agriculture 289 Vegetables and arboriculture 295 Textile agriculture 299 Food preparation 299 Food preservation 303 Drink and drugs Agriculture (food and clothing) products and activities – an overview 310 Leather, textiles, and fabric 310 Skin and fur production 310 Textile production 312 Processing of basic materials 312 Trees, lumbering and woodworking 314 Metallurgy 329 Products of the processing of wood, stone, leather, skin 329 Weapons and warfare 335 Transportation 335 Draft animals 345 Vehicles 355 Numbers and measures 355 Ordering of time 369 Discussion: Vocabulary

6.5.3 6.5.4 6.5.5 6.5.6 6.5.7 6.5.8 6.5.9 6.6 6.6.1 6.6.2 6.6.3 6.6.4 6.6.5 6.6.6 6.7 6.7.1 6.7.2 6.7.3 6.8 6.8.1 6.8.2 6.9 6.9.1 6.9.2 6.9.3 6.10 6.11 6.11.1 6.11.2 6.12 6.12.1 6.13 7

309

Concluding chapter: an integrated view of the linguistic and cultural histories of Eurasia 378

Literature

387

Appendix 1: Languages of the current atlas

401

Appendix 2a: Grammar: Features, complete list (from DiACL) Appendix 2b: Grammar: State combinations

411

Appendix 2c: Grammar: State combinations in languages Appendix 2d: Grammar: Solutions 1–10 by Structure

433

414

426

Appendix 3a: Lexicon: list of concepts, coverage by family Appendix 3b: Lexical data

405

430

xxxii

Contents

Appendix 3c: Lexical data: statistics

695

Appendix 3d: Lexicon: Source language data, flow map Appendix 4a: Language consultants Appendix 4b: Literary sources

707 719

Appendix 4c: Geographical sources Map Credits Index

720

723 723 Subjects Authors/Resources 726 Languages

705

726

703

1 Introduction 1.1 Why an atlas of languages and cultures? The Mouton Atlas of Languages and Cultures provides the reader with empirical data, maps, visualizations, and analyses, which indicate the geographic distribution, the classification, and the typological patterns of linguistic features. In this aspect, the Mouton Atlas follows in the tradition of earlier works in the genre, such as the The World Atlas of Language Structures (Haspelmath 2005) or The Atlas of Pidgin and Creole Language Structures (Michaelis et al. 2013), which all use geography as an overarching principle for visualizing and examining language diversity. The fundament of resources such as these are extensive databases with linguistic data (lexical, grammatical, typological, or phonological) (List and Cysouw 2016, Forkel et al. 2018, Hammarström, Forkel, and Haspelmath 2017), which provide an important basis for empirical and quantitative studies on language diversity. Similarly, extensive databases with ethnographic or other types of data, such as climate or ecology (Kirby et al. 2016) are used in addition to linguistic data to test hypotheses and causalities of language diversity and change. This research represents a new wave of a pronounced empirical research, where the fundament is consistituted by an observation or characterization of features, which can be analyzed by quantitative methods (e.g., Greenhill et al. 2017, Hammarström 2016, Cathcart et al. 2018). This atlas joins this research in that it primarily investigates language, more precisely morphosyntax and lexicon, by means of identified features, which are mapped in geography, analyzed phylogenetically and statistically, and contrasted to other data types, such as ethnographic data (e.g., Jordan 2007). However, the current atlas also follows in the footsteps of a much older tradition: historicalcomparative handbooks on the aspects and consequences of language reconstruction, such as Reallexikon der Indogermanischen Altertumskunde (Schrader 1923, 1929, 1917), Indo-European and the Indo-Europeans (Gamkrelidze and Ivanov 1984, Gamkrelidze, Ivanov, and Winter 1995) or A Dictionary of Selected Synonyms in the Principal Indo-European Languages (Buck 1949). Like the atlases and database resources mentioned in the previous paragraph, these handbooks are based on large amounts of empirical data and observations based on many languages; however, their main objective is observation, reconstruction and description, not quantification and statistical testing. The historical-comparative method and reconstruction, interpreted in a cultural context, outdo the methodological fundament for these handbooks. In this sense, the current atlas can be viewed as a hybrid work: part atlas, part database description, part explanatory textbook, which is part comparative-historical and part statistical-evolutionary in ist methodological baseline. An important aim of the atlas is to contextualize both the empirical input data as well as the results. Therefore, the atlas does not aim at a cross-linguistic, ‘universalʼ coverage (even within a specific area), which is an important difference to resources such as WALS. First, the atlas targets a cohesive, delimited geographic area for study. The area is partly based on the extension of one family, Indo-European, which is treated as a whole, and includes isolates and languages of other families that are spoken close to Indo-European. Second, the atlas moves outside of expected cross-linguistic domains in the selection of features. In morphosyntax and typology, the volume includes features, which can be specific and unique to the area. In the lexicon, the volume moves outside of basic vocabulary and into culture vocabulary, which is adapted to the reality of the targeted area. A second important aim of the atlas to investigate diachrony, which continues the tradition of comparative-historical linguistics: for all targeted features, data from ancient lanugages are systematically included. Ancient language data is held in high esteem within the historicalcomparative tradition, which often, on the other hand, pays less attention to data from living daughter languages. The current atlas aims to include both: analysis, maps, and results are based on historical and contemporary languages alike. For the purpose of clarity, contemporary https://doi.org/10.1515/9783110367416-001

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1 Introduction

and historical data are displayed on separate maps; in analyses and statistical tests, they are treated together. The atlas is based on two types of data: grammatical and lexical data. Accordingly, the volume is divided into two main sections, one dealing with grammar data, one dealing with lexical data. The introductory and concluding chapters aim to connect these two sections and to evaluate and explain results in a cultural context, which is an overarching theme of the volume. All maps, visualizations, and results are based on empirical data extracted from a database DiACL – Diachronic Atlas of Comparative Linguistics (Carling 2017a, Carling, Larsson, et al. 2018). The database design is a fundament to the extraction of datasets and mirrors the models and methods used in the atlas; therefore, parts of the introduction of the respective grammar and lexical data sections will deal with the database organization and design as well as coding policies. Frequently, the volume contains exact references, for instance in the form of ID numbers, to the database. On the other hand, the volume offers a substantial addition to the content of the database, both in terms of explanations, interpretations, and references. The database and the printed book are symbiotic, but the information of the book is permanent and controlled, whereas large parts oft he database is still impermanent and non-controlled, reflecting work in progress. The remaining parts of the introductory chapter 1 will describe the main aim, the setting, the languages and families, and the policies for geograpic reproduction and orthography in the atlas. Chapter 2 will outline the theory, model and method underlying the selection and evaluation of features. Chapter 3 will overview theories and models on language classification and change. Chapter 4 will describe the database infrastructure of Diachronic Atlas of Comparative Linguistics, including database structure, design, and coding policies. Chapters 5 and 6 constitute the core parts of the volume, dealing with the grammar and lexicon parts respectively. Finally, chapter 7 concludes and summarizes the results of the volume, trying to connect the grammar and lexicon sections from various perspectives. The remaining part of the volume is constituted by appendices (numbered according to chapters). These represent the different sections and include languages, language metadata, grammar features, grammar data, grammar solutions, lexical data, lexical statistics, sources for specific maps, list of language consultants, and literary data sources (language data and geographic data).

1.2 Defining our aim: observing language variation by empirical methods Languages change, consistently and inevitably. Words become lost, emerge, or change their meaning. Grammars change; categories appear, disappear, or their function changes. Syntactic patterns change – the rules and mechanisms for using grammar and words in their context become modified. Cultural systems also change. Artifacts stop being used, new ones are invented, or the form and function of the old ones become adjusted. When cultural systems and rules change, new principles are established; and hierarchies, patterns and applications are modified. In the process of cultural adjustment and change, language changes, too. Every cultural innovation, be it a modification, a gain, or a loss, involves an adaptation of the language: the invention of a new artifact, a social rule, or a cultural habit requires a new name of it, and the process may lead to the abandonment of an obsolete artifact, social rule or cultural habit – which in turn leads to a change in the name of it. Every new generation inherit the patterns of a previous generation – not as an exact replication, rather as a ‘descent with modification’, through which the most adapted is continued (Darwin 1859), which, when transferred to culture, is labelled cultural evolution (Cavalli-Sforza and Feldman 1981, Boyd and Richerson 1985), and further to language as culture-language evolution (Kirby, Dowman, and Griffiths 2007). Over time, this consistent, dynamic change leads to variation and diversity, beginning with the smallest entity of culture and language and gradually spreading over large areas. Variation

1.2 Defining our aim: observing language variation by empirical methods

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is a reality, present within language families, sub-branches, languages, linguistic subsystems, dialects, ethnolects, sociolects, genderlects, or familylects, as well as cultural units, ranging from villages to large areas. Diversity is another dimension of this reality, present in geography, from forest villages, valleys, islands, or plains, to over entire continents. However, even though linguistic and cultural change can be described as uncultivated garden, where each item of language and culture changes along its own paths, it is not random either. A large number of factors constrain change. The first and most important of these constraining factors is environment. In the strict sense, the environment involves the physical surroundings of a language or a culture: climate, soil, living conditions, flora, and fauna. Languages and cultures carefully adapt to their surrounding environments, and integrate items as symbolic artifacts in their shared linguistic and cognitive systems (Sinha 2014). In the case of a relocation of a group, for instance caused by starvation or expulsion, the linguistic and cultural systems of the migratory group quickly adapt to the new environments, resulting in a change. From a larger perspective, topography and climate shape and constrain language change. Open plains and other easily navigable terrains become spread zones, where languages spread and change faster. These areas are characterized by lesser genetic density and structural diversity, and shallower (and more easily recognizable) language families. Mountainous areas, dense forests and other areas of high topographic resistance become divergent zones, where language change is more constrained. These areas are characterized by high genetic and structural diversity, and deeper (and less easily recognizable) language families (Nichols 1992). The second factor is salience, which can most easily be described as the functionality or economy of usage of a pattern or an item (Epps 2014). Over time, economy, functionality and frequency of usage constrain systems. Analogy, frequency and economy causes grammatical leveling; iconicity and phonemic economy harmonize sound structure. Frequency of usage of cultural patterns relate to their functionality, as does their symbolic representation in language. The affordance of artifacts affects their applicability, directing language. Therefore, a linguistic representation, like a cultural habit, may remain unchanged for long periods, provided that the linguistic or cultural functionality continues, unchanged, despite changing circumstances. That said, systems might display striking divergences from these general preconditions. Systems may develop extraordinary, redundant, and complex patterns; which cannot be explained from any functionality or habituality perspective. Patterns of taboo and superstition, or art, decoration patterns, complex rituals, and so forth may elude any functional explanation; yet they may be repeated and replicated, generation after generation (Dunnell 1978, Shennan 2008). Redundancy in expression may stand out as unexplainable from an economy or frequency perspective, yet it may be both frequent and stable. Much of the explanation for the changing behavior lies in the causalities of change (Croft 2000). Fundamentally, change per se is not an inherent property of either language or culture: change has a cause, a driving force, such as an adaptation to a previous or simultaneous changing circumstance. What are these causalities of change? In particular, relocation is a fundamental cause for change. Relocation leads to changing environment, and changing environment leads to change in linguistic and cultural adaptation. Another impacting factor is contact. Whatever the nature of contact, the outcome will be a change. Contact, both linguistic and cultural, is typically characterized by geographic proximity, but it may also reach over larger areas and may be mediated by a third party. Contact may be one-sided, mutual, or multifaceted, and it may be exercised between populations, which are equal or unequal in terms of size, power, or cultural impact. Contact, in language and culture, often leads to convergence, meaning that diverging or varying patterns become more similar. A word, a grammatical pattern, a cultural practice or an artifact is transmitted from one group to the other, and the outcome is a shared pattern, linguistic or cultural. Furthermore, every change builds upon a previous one. The snowball-like effect of continuous change, often unconscious to speakers and cultural practitioners, is known as drift; a change

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which often happens in parallel between related, but diverged systems, sharing a habitat but not necessarily in frequent contact with each other (Sapir 1921, Chang et al. 2015). Parallel drift is a vigorous factor in the shaping of linguistic and cultural patterns: this process embodies cultural and linguistic, as well as environmental adaptation, just as much as it encapsulates previous change. Use of extensive, empirical data, hypothesis testing and the use of statistical models are fundamental aspects of cultural and linguistic evolutionary research (Cavalli-Sforza and Feldman 1981, Dediu and Levinson 2012). On the other hand, evolutionary approaches to language and culture, being basically humanistic disciplines, do not require statistical models, and a large body of scientific production within the area does not apply mathematical models at all (cf. Shennan 2008). A prerequisite for applying quantitative models is, besides hypothesis formulation, data quantification. The approach of this volume is leaning towards a quantitative model of cultural and linguistic evolutionary research. However, reducing the dynamic complexity of language and cultural structure into numbers is not a trivial task. The current volume will aim towards facing this dilemma. This means, the book discusses theories, problems, methods, and models that involve the process of transforming complex relations of language and culture into quantitative units, i.e., features, characters, traits, which may be used as a basis for formulating and testing hypotheses by statistical models. The data amassed in the project is statistically analyzed to summarize, cluster, identify patterns in the data, in particular to enable geographic mapping. All data, and its coding, is given in the appendices of this book. The data is also available for downloading of quantitative sets in the database DiACL – Diachronic Atlas of Comparative Linguistics, which is the basis for the current volume.

1.3 The setting: Eurasia from the Neolithic revolution to the Industrial Age The current atlas aims at capturing the dynamic diversity of a changing linguistic landscape stretching from the British Isles and continuing over Eurasia to Southeast Asia. The period we are dealing with in principle begins with a significant and revolutionary change, the Neolithic agricultural revolution, 11–10,000 BP, and stops before the Colonial Era and the Industrial Revolution in the last centuries – another significant and groundbreaking change, for which we cannot predict future impact on languages and cultures. This policy has several implications. First, we include as much language material as possible from ancient sources to contemporary states of languages, but our target is set to the languages and cultural systems of pre-industrial and pre-colonial societies, which means, for instance, that wo do not include concepts and cultural properties which we classify as ‘modern world’ (cf. Buck 1949, Tadmor and Haspelmath 2010). In addition, our geographic location of languages does not include their post-colonial extension, meaning that, e.g., English is spoken only on the British Isles, Portuguese and Spanish only on the Iberian Peninsula, and French only in France. Given our policy to render modern languages as polygons, we are aware that this is not a trivial task. Our contemporary-based polygons, of, e.g., Armenian, Kabardian, Russian, Kurdish, or other languages whose extension has changed several times in the past hundred years, are not representative of a pre-colonial extension in the manner that, e.g., English is. With this caveat in mind, we believe that polygons are still much more representative for mapping than focal points (see 1.5 for polygon policies and appendix 1 for language metadata). The area spans over several climate zones, several language families, and a wide range of diverging cultural areas. Following the geographical classification by D-PLACE (Kirby et al. 2016), our atlas encompasses the areas (from Northwest to Southeast) Northern Europe, Middle Europe, Southwestern Europe, Southeastern Europe, Eastern Europe, Caucasus, Western Asia, Middle Asia, and the Indian subcontinent. In terms of climate zones (cf. Peel, Finlayson, and McMahon 2007), our area encompasses a substantial variation in the climate, ranging from the boreal, fully humid and cool summer areas

1.4 Languages, language families and cultural groups in our data

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Map 1: Topographic map of the macroarea covered in our data, with the particular projection (customized Albers projection) used in this atlas.

of the northern parts of Northern Europe and Eastern Europe; boreal, fully humid, and warm summer areas of Eastern Europe; warm temperate, fully humid, and warm summer areas of Northern and Middle Europe; warm temperate, dry and warm summer areas of Southwestern and Southeastern Europe (in our descriptions normally referred to as Mediterranean) and substantial parts of western Western Asia; arid, dry winter, hot areas of eastern Western Asia; and equatorial, dry winter and equatorial, monsoonal areas of Indian Subcontinent.

1.4 Languages, language families and cultural groups in our data Language is a fundamental common denominator in this atlas, and language is used as basic classification basis for all data. This is not new: besides geography, language is typically used as a metric to classify cultural groups (Murdock et al. 2008, Kirby et al. 2016). Our aim of data compilation has been to cover – for our selected setup of features and concepts – all living and known extinct languages in our targeted area. In this aim, we have almost been successful; however, there are lacunae in the corpus: either entire languages missing or specific data types (typology, basic vocabulary, and cultural vocabulary) are missing for certain languages. These lacunae have various causes, either shortage of time, shortage of subsidy, or unavailability of expertise. In particular, ancient languages may potentially contain missing data: the sources are given beforehand and cannot be completed by information retrieved from native speakers. We have tried to deal with this in a manner that modern and ancient languages can be compared on equal terms to contemporary ones (chapter 4). In our current overview, we will include languages with data of any type, for the various types, i.e., grammar, basic vocabulary, and culture vocabulary; we refer to the respective sections of the atlas (chapters 5 and 6). A complete list of languages and their classification is given in appendix 1, along with language metadata. Location by family and branch (for Indo-European) is shown in maps 2a (contemporary), 2b (historical) and 2c (Romani chib). Even though our atlas incorporates – as far as possible – small and minority languages of various regions, it is obvious that linguistic diversity is unevenly spread over the geographic landscape. The correlation between geography and linguistic diversity, also at the level of grammar, is evident from the map distribution. In general, regions with high-resistance topography (high mountains, dense forests), become areas where language diversity is higher, indigenous languages have an immeasurable long local history, and languages are typically not spread beyond the specific area by linguistic affinity. In our atlas, this definition targets, e.g., the Caucasian mountains and the Basque country. These regions are

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traditionally labelled as residual or accretion zones. The other type is labelled spread zones. These areas are generally larger, they are characterized by low-resistance topography (open plains, tundra, and farmland), linguistic diversity is lower, languages do not necessarily have an very long local history, and in general individual languages, as well as branches and families, occupy larger territories. (Nichols 1992, Nichols 1997). We will look more carefully at these classifications in this volume. Moving over to cultures – what metrics do we use to classify them? This is an old dilemma. In empirical, large-scale ethnographic studies (Murdock 1969, 1981, Lomax et al. 1977), language is often used as a basis for identifying cultures, for which cultural patterns are then identified by various metrics, such as subsistence mode, kinship, or marriage rules. However, as we move into prehistory, the identifier language becomes more and more uncertain, even though in scientific literature within disciplines dealing with prehistory, language or the concept of language families are often transferred to describe observed patterns, such as in pottery (Hornborg 2005, Hill and Hornborg 2011). Cultural or ethnographic identification is a complex issue, and implies a substantial amount of often contradictory parameters, which make identification complex. Just as with language, location in space and time are decisive in cultural and ethnographic identification and classification, also targeting archaeological cultures. Besides linguistic affinity, other classificatory parameters (Murdock et al. 2008) include ethnonyms, both alternative names bestowed by selves as well as names by others, meaning of ethnonyms, cultural affiliations with other cultures or culture areas, as well as affiliations to prehistory. Ethnographic data is constituted by descriptions and identifications of various cultural patterns. Besides spatial and temporal definition, as described in previous paragraph, two classificatory parameters are considered to be of primary value: kinship and subsistence (Lomax et al. 1977). In classifications, such as the subject-indexing system used by HRAF, Outline of Cultural Materials (OCM) (Murdock et al. 2008), subjects are classified and enumerated by main cultural categories which are classified by more and more fine-grained categories, such as ‘Food quest’, ‘Animal husbandry’, or ‘Clothing’, which in turn are classified into ‘Food quest: Hunting and Trapping’, or ‘Hunting and Trapping’ which may be described as ‘Animals sought; hunting methods and techniques (e.g., stalking, collective drive); description and use of traps and snares; use of domestic animals (e.g., dogs, ferrets); special elaborations (e.g., trapping for the fur trade); hunting trips; economic importance of hunting; organization of labor and division of catch; associated beliefs and practices; hunting for sport; regulation (e.g., game laws, open seasons); etc.’, and so forth. Just as with language, ethnographic classification is about making generalizations of observed patterns, label them, classify them, and organize them hierarchically. In quantifications of ethnographic data, a classification system is decisive. An important fundament to ethnographic empirical data is D-PLACE (Kirby et al. 2016), which is a database of geographic data (location), linguistic (language classification), cultural and environmental data (as identified hierarchical features), organized as downloadable datasets. D-PLACE and another similar resource, HRAF (The Human Relations Area Files) (http://ehrafworldcultures.yale.edu), are both based on a classification system of cultures and cultural features which was established by George P Murdock and his team in the 20th ct. (Murdock 1969, Murdock et al. 2008), which has been expanded by the language classification system of Glottolog (Hammarström, Forkel, and Haspelmath 2017). The classification system of Murdock has served as a fundament to our classifications and labeling of categories (see further 6.3). The database DiACL (see 4) is based on language as a fundamental unit of classification. The database contains only linguistic data, but, by the systematic and large-scale compilation, organization, and classification of culture vocabulary data, our database targets cultural classification, which is an overarching theme in this volume. In classifying and standardizing the cultural vocabularies, the OCM standard (Murdock et al. 2008) has been an important metric, and the cultural descriptions, contemporary as well as past, have served as a guideline for identifying and establishing the list of cultural concepts that we use in our culture word lists (6).

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Map 2a: Living languages with data in our corpus (for abbreviations see introduction, for metadata see appendix 1).

1.4 Languages, language families and cultural groups in our data

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Map 2b: Historical languages with data in our corpus (for abbreviations see introduction, for metadata see appendix 1).

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Map 2c: Romani languages with data in our corpus (for abbreviations see introduction, for metadata see appendix 1).

1 Introduction

1.6 Orthographic policy for languages of our corpus

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1.5 Language extension: policies for rendering language extension by polygons in the atlas Spatial extension is important in our data. However, our policy to render languages by their precolonial extension sometimes clashes with our policy to give polygons of contemporary languages by their present extension. Geographic extension of languages, either by a focal point indicating a central area for the language (extinct languages and Romani dialects in our data) or by a polygon, indicating the full extension of a language, is very problematic. Languages continuously change their location, and maps quickly become outdated. Nevertheless, it is of high value to show diversity by polygons rather than by focal points: with focal points, languages such as Russian and Kabardian appear as equal in size, with polygons the difference is more evident. Due to the circumstances, we have been forced to adapt different policies for polygons. When it comes to reliable maps, most available data from Eastern Europe, West and Central Asia is from before 1990, in particular for languages within the former Soviet Union. Therefore, most of our sources for polygons represent a situation which is before 1990. For other languages, such as Yiddish, our polygons represent a situation which is older than WWII. Our sources for polygons are given in appendix 4c. In case of overlapping polygons, smaller polygon areas consistently overlay larger ones. Another issue is the projection of our maps. Since we lack data from Siberia as well as from Africa, we have created a specially designed map projection. Our area spans over large parts of the northern hemisphere. We have used the geographic coordinate system “WGS 84” (EPSG: 4326) as a worldwide standard as base; for a good representation and fit in the maps we have adapted a customized Albers projection (Central Meridian: 25° E; Latitude of Origin: 30° N; Standard Parallels: 35° N and 65° N). The Albers projection is an “equal-area” projection, showing the correct size of an area (polygons), with low distortions of shape and scale between the standard parallels.

1.6 Orthographic policy for languages of our corpus Our corpus encompasses a large amount of data from languages using different writing systems. For some languages, the orthography is not set, and there is no unified orthographic convention available. To harmonize this inconsistency has been a very complex task, in particular for languages that have complex phonemic systems. We have aimed at using conventional orthography throughout the book, basically leaning towards the standard dictionaries for languages. We have also aimed at harmonizing the orthographies within languages, in cases where different dictionary resources use different conventions. Only as an exception, we use IPA. We also use Latin script for all languages except for Greek. For our orthographic conventions for Caucasian languages, see Orthographic conventions (Front matter).

2 Theoretical backdrop: words, things, and humans in their environment 2.1 Sociocultural reconstruction Sociocultural reconstruction deals with the reconstruction of the human past, a scholarly discipline, which bases conclusions on available data, gathered from multiple disciplines. At the center of the sociocultural reconstruction, we aim at patterns of human behavior, and these patterns can be reconstructed using a wide range of resources. We may use linguistic data, i.e., data from grammars, dictionaries, or from fieldwork. We may also use archaeological data, as well as contemporary or historical ethnographic or anthropological data, compiled from historical sources or from fieldwork. Language, archaeology, ethnography, and anthropology are the core disciplines of sociocultural reconstruction, which have a natural relation to environmental data, such as paleoclimate. The core issue in sociocultural reconstruction is what we do with our data and what possible interpretations and conclusions we draw from them. In all research aiming at the human past, a sound methodology is crucial: the material is often vulnerable to gaps in interpretation, which may lead researchers in wrong directions. A predetermined view on the expected outcome or a strong theory-based bias may lead to over-interpretation or pushing of the data in the direction of the theory. This is of particular importance in research in several bordering disciplines, and most importantly, it is a problem that statistical models cannot solve. The current volume deals mainly with linguistic data, and reconstructions of the past are based on data from languages. For reconstructing the past, we put language into a framework of ethnography, archaeology, and occasionally mythology. Sociocultural reconstruction by means of large-scale data, linguistic as well as anthropological, dates back to 19th century disciplines of historical linguistics and anthropology, performed by scholars such as Jacob Grimm, Hugo Schuchard, and Rudolf Meringer for linguistic reconstruction (Schuchardt 1912), and scholars such as Fritz Graebner or Peter Murdock for the reconstruction of ethnographic data (Graebner 1911, 1924, Hudson, Ford, and Murdock 1945). The framework of words-and-things theory, which forms the basis for the discipline of paleolinguistics or linguistic archaeology, is typically philological or qualitative in its nature; the reconstruction of individual words and their postulated ancient meanings or meaning changes are used in comparison to, e.g., evidence from archaeological and ethnographic data (Hock 1991, 573–578, Epps 2014, Benveniste and Lallot 1969a, b). An important part of this research is to reconstruct the meaning and use of reconstructed words in proto-languages, a type of research that is not without objections in the scholarly community (Heggarty 2014, Anttila 1989). Another important area is the reconstruction of pre-historic language contact, by means of identifying loans between languages in prehistoric stages of languages (Hock 1991). Even though the words-and-things theory serves as a natural backdrop to our approach, our take on the issue is fundamentally different: we aim at investigating patterns of human past, basically at using a quantitative perspective, which brings us closer to quantitative approaches to cultural evolution (Cavalli-Sforza and Feldman 1981, Gray and Watts 2017). This has multiple implications. As an example, if we are hesitant about the reconstructed meaning for a specific concept, we may look at all meanings, meaning changes, and colexifications (i.e., polysemous meaning patterns for lexemes) for this concept in all languages of a family, not for, e.g., a selected cognate set. Given that the attested meaning changes and colexification patterns in attested languages demonstrate a clear pattern and predictable, how likely are unpredictable changes in prehistory? And, if we assume unpredictable changes, can we motivate these exceptions by extraordinary changes in our data? By a quantitative take on sociocultural reconstruction follows a certain number of theoretical preconditions. The first is the principle of uniformitarianism: if we reconstruct prehistory on the https://doi.org/10.1515/9783110367416-002

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basis of history, using a quantitative model that predicts the non-attested past from an attested history, then we have to assume that linguistic processes taking place at present or historically are the same as those which operated in prehistory (Labov 1972). The second precondition is hypothesis formulation: we have to formulate hypotheses – be they the behavior of various features, or predictability of certain events – in order to test, statistically, whether our hypotheses match our predictions. Hypothesis formulation guides our compilation, organization, and curation of data. As mentioned earlier, we assume that cultural and linguistic change is implicitly connected. Further, we assume that multiple factors constrain their behavior; an important factor we define as salience. By salience we incorporate a spectrum of functions or properties of linguistic and cultural features, such as frequency and economy for grammatical features, functionality and economy for cultural behavior, and functionality and affordance for cultural artifacts (Carling 2013, 2016, Epps 2014). Properties of salience are important, even necessary, to uphold and continue structures. It is their everyday use, in present as well as in the past that forms the basis for our identification of patterns, which we assume to be of high age and stability. The identification of these patterns, within or between ethnolinguistic populations, over smaller or greater areas, form the basis for establishing cultural matrices. These are defined as dynamic and varying conglomerates of cultural and linguistic patterns, simultaneously existing at macro- and microlevels, mutually hooking up on each other, and forming identifiable patterns in time and space (Hill and Hornborg 2011). Even though we take an uniformitarian perspective to change, where the present reflects the past, we admit that change is not a gradual process, operating at an even pace. Rather, change, both in language and in culture, evolves in bursts (Greenhill et al. 2010). Significant innovations in culture, such as ground-breaking inventions, or environmental factors, such as war, disease, starvation, or migration, may change the preconditions for sociocultural salience completely.

2.2 Models and methods for organizing and selecting data Through implementing a matrix of quantification of linguistic data, also using ancient sources, we make use of Meid’s space-time model (Meid 1975). This model sees a reconstructed language (Proto-Indo-European in the model) as a language with dialects and variation, whose evolution can, at least in theory, be stratified and transferred to time and space, based on available documentation. With an increasing time-depth, the basis for a space-time reconstruction shrinks. We transfer and expand this model to a quantified scenario, where we build a matrix of coded data and metadata, including reliable spatial and temporal information for languages (see 4.1), the central unit in our classification. Beyond the historical, attested language states, we also include reconstructed states, as long as we are confident about the certainty and reliability of the data. Generally, we include reconstructed lexemes (derived by the comparative method), but not morphosyntactic units, and we include reconstructed meanings only when we are confident about their reconstruction. Taken together, the compilated and quantified data represents a matrix of attested and reconstructed language data by means of traditional methods, i.e., observation and reconstruction by the comparative method. Further, we compile metadata, i.e., information about how languages are attached to space and time. This can be used to reconstruct conditions and events of the non-attested past, both by traditional and by evolutionary methods, by applying a unifomitarian approach. In this volume, we aim at two types of data, grammatical and lexical. Within a words-andthings theory, vocabularies, their behavior, reconstruction, colexification patterns, and semantic changes, have a vital role in sociocultural reconstruction. But what about grammar? If our aim is sociocultural reconstruction, why do we compile grammars? Grammars, with the exception of specific cultural usages in different settings, in general have little relevance to culture-specific

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practices (Epps 2014). However, grammar is a powerful instrument for tracing language evolution and change, as well as for tracing contact between populations beyond the attested history. Language shift, processes of creolization, code-switching, convergence, advergence, drift – all these are processes which can be traced and understood well through grammatical data, preferably in combination with lexical data (Epps 2014, O’Connor and Muysken 2014, Muysken 2012). Sociocultural patterns are mirrored in vocabulary, and sociocultural change has a direct impact on the vocabulary. Grammar, on the other hand, adheres words together, and therefore, any change in vocabulary also implicitly has an impact on grammar.

3 Language: classification, reconstruction, and principles of change 3.1 Principles of change Language change involves various processes, creating a variating outcome (fig. 1). Divergence is a process by which a coherent language splits up into two (or more) groups, separated by geography, which over time results in two (or more) distinctly different populations. Convergence is a process where two (or more) distinctly different languages become more similar over time, sharing an increasing number of traits. This process may have several causes, of which language contact is most dominant (Renfrew 2000, 12 ff.). Another important characteristic of change is drift, defining the natural, unconscious change, or an inherent predisposition to undergo certain changes (Sapir 1921, 149–152, Chang et al. 2015, 202–203). Parallel drift or advergence is a process which gives a result similar to convergence: languages evolve in parallel, typically sharing a common ancestor, keeping mutual contact, and over time developing in a similar direction (Chang et al. 2015 ff., Renfrew 2000, 14). DIVERGENCE

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Accordingly, there are two models for classifying languages, which are related to these principles of change (fig. 2): the tree model, based on the principle of divergence, which classifies according to splits, and the wave model, which illustrates the effects of convergence and advergence over time. Both models are equally important in explaining variation and classifying languages, and both models can be used to describe the evolution of languages and dialects, as well as linguistic subdomains, down to the most fine-grained level of individual traits (Meillet 1925, 48–52, 1921, 61–75). Under these conditions, language change comes out a complex process, occurring at different levels and along various parameters, and affecting parts of language differently. Various (sub)domains of language, down to the level of individual traits, have different inherent propensity to change, which are fundamentally constrained by their role in language, culture and society. Even though there is no single subdomain or trait of language that is irrefutable to change, fundamental differences in change patterns exist between traits, such as lexical concepts or typological properties, which may be constrained by different factors. This inherent complexity of change is the main obstacle to the identification of a universal model for language classification. One model based on a specific type of language material might be vulnerable to contrary arguments supported by other language material.

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3 Language: classification, reconstruction, and principles of change

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3.2 Comparative and evolutionary models of reconstruction The two main methods for reconstructing language change, the comparative and evolutionary methods, share similarities, but there are also important differences in terms of both the general view on reconstruction as well as data compilation, working procedure, and instruments of analysis. The foundation for reconstruction by the comparative method, as outlined already in the early 19th century, is a systematic matching of sound correspondences between languages, based on lexical and morphological cognates (Weiss 2014), addressing issues of horizontal transfer that might create noise in the reconstructions, such as borrowing, sporadic sound change, or analogy (Hale 2014, 146). The foundations of the comparative method are the principles of regularity of change, arbitrariness between form and meaning, and a predictable directionality of change. Evolutionary methods, on the other hand, base their classification on measuring substitution or pairwise mutual dependencies of binary data sets, and even though the results often are similar, the way in which they are achieved can be entirely divergent. A conceptual basis for comparative and evolutionary linguistic methods is the definition of a trait. Traits can be either phonemes, grammatical/lexical morphemes, morphosyntagms, or comparative concepts, and they can be either homoplastic, i.e., traits may share similarity independent of lineage, or they are homologous (Nichols and Warnow 2008, 765, Chang et al. 2015, 202), i.e., their shape is entirely governed by lineage. The trait type comparative concept (Haspelmath 2010), is an abstraction or generalization of an observed pattern in language, which may recur cross-linguistically, independent of lineage (Nichols and Warnow 2008, 764–766). Comparative concepts are by nature homoplastic, but in comparative method, typological traits are constrained by their morphology (Hale 2014, 156–158), which are by definition homologous, i.e., they are unique traits, the shape of which is governed by inheritance from a predecessor. Here, the linguistic definition is slightly different from the biological definition of homoplasticity, which refers not to characters abstracted away from their instantiations, but to instantiation of character states in specific taxa. The trait type cognate, or etymology in comparative linguistics, is a grammatical or lexical morpheme, which shares similarities in its phonemic structure with a morpheme in another language, and which depends on shared ancestry (Mailhammer 2014, 424 ff.). Cognate traits are homologous, and usually come into existence only once (Chang et al. 2015, 202), when they are initially created (e.g., by morphological derivation). In comparative linguistics, the common precursor has the form of a reconstructed morpheme, marked by an asterisk. Lexical cognates and sound correspondences in comparative method are in a mutual relationship: cognates confirm sound correspondences, and sound correspondences confirm cognates.

3.3 Grammar: reconstruction and principles of change

19

3.3 Grammar: reconstruction and principles of change Like lexical data, grammatical data is vital to language classification and reconstruction. However, the principles for classification and reconstruction are in some sense different, due to the functional nature of grammar. Grammar consists of three components that can be used for classification or reconstruction: morphology, morphosyntax and syntax. When abstracted into structural concepts or features, morphology, morphosyntax, and syntax can be compared, contrasted and quantified as typology. In particular typology has proved to be very useful for characterizing language diversity and classification (Greenberg 1966, Comrie 1989, Nichols 1992, Dediu and Cysouw 2013). In the early days of comparative linguistics, scholars attempted to reconstruct grammar of proto-languages based on morphosyntactic reconstruction, applying the same rules as for lexical reconstruction (Brugmann, Delbrück, and Delbrück 1893, 1897, 1900, Osthoff and Brugmann 1878). In this reconstruction, high value was attributed to data from ancient languages, such as Sanskrit, which were considered to be closer to the primeval system of the reconstructed language. Much focus was laid on reconstruction of formal systems, i.e., the reconstruction of morphological material into a syntactic frame, aiming at revealing complete and functional systems of a proto-language. However, the method turned out to create greater uncertainty than phonological and lexical reconstruction (cf. previous chapter), due to the higher abstraction of grammatical function combined with the uncertainty of directionality in grammar change. An example is the Indo-European alignment system. During the 20th century, using a combination of morphological reconstruction and syntactic frames, all types of typological systems, from nominativeaccusative, ergative, active, and isolating, were proposed for the Indo-European alignment system (Hirt 1934, Klimov 1974, Gamkrelidze, Ivanov, and Winter 1995, Klimov 1971). A fundamental roadblock in morphosyntactic reconstruction involves the correspondence problem (Roberts 2007, 363–367): a pattern in a proto-language may be reconstructed on the basis of the patterns in daughter languages, providing that the genetic relationships are known. However, the problem in case of a discrepancy is deciding which pattern should be preferred: the presence of a specific pattern in a majority of the daughter languages may not be indicative of the original distribution in the parent language. Morphological components between languages may be in a cognate relation, i.e., their phonological structure and their function can be reconstructed back to a common precursor. However, combinations of morphemes, or morphological material in a syntactic context, such as alignment or word order, cannot be regarded as cognates: therefore, morphosyntactic units are not comparable to lexemes, compounds or phrases in terms of reliability of reconstruction. There is considerable debate on this issue in linguistic literature (Jeffers 1976, Lightfoot 2002, Campbell and Harris 2002), but typically, a higher reliability is found among reconstructions of paradigmatic type, e.g., case systems or conjugation systems, than reconstructions of syntactic type, such as word order (Walkden 2013). This observation is important: we may observe a difference in behavior of paradigmatic and non-paradigmatic features also in our data. Grammar may also be reconstructed using evolutionary methods. Here, the concept of using typological comparative concepts, i.e., abstractions of grammatical patterns that are comparable cross-linguistically (Haspelmath 2010), is particularly frequent. The probability of a syntactic pattern to be present at an ancestral proto-language is estimated on the basis of a tree topology, the distribution of the feature among the daughter languages, and an evolutionary model of change (Maurits and Griffiths 2014, Cathcart et al. 2018) (see 5.7.2). Just as with grammatical reconstruction, there is a considerable debate as to whether grammatical structure is a valid instrument for language classification. As has been demonstrated in numerous studies, typological patterns are not arbitrary: they cluster with respect to family as well as with geography (Nichols 1998, 1992). However, the causalities of similarity in patterns of grammar between languages are not clear; both areality, convergence, lineage specificity, and

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3 Language: classification, reconstruction, and principles of change

parallel drift have been suggested (Baker 2011, Croft et al. 2011, Dryer 2011, Dunn et al. 2011, Longobardi and Roberts 2011, Cathcart et al. 2018). This matter is vital to classification. For the lexicon, language contact and cross-language or cross-family borrowing can be traced by means of phonemic reconstruction and relative chronology. For typological features, being abstractions of grammar for the purpose of cross-linguistic comparison, this is only to a limited extent the case. Typological patterns are parts of language that may be stable or unstable, depending on various factors (Cathcart et al. 2018), but which may, when compared on a mass scale, give important indications about previous and contemporary language spread, diversity, and change. Therein lies the importance of typological data of a study such as ours, which aims at a deeper understanding of prehistoric changes, contacts, convergences or isolation, aiming at a large timespan and an extensive geographic area.

3.4 Lexicon: classification, reconstruction and principles of change Principles of lexical change form the basis for lexical reconstruction and classification. A precondition for lexical change is polymorphism or colexification, i.e., the synchronic co-occurence of meanings of a lexeme (François 2008). The occurring types of semantic relations in synchrony, e.g., metonymy, synonymy, hyponymy, antonymy, and meronymy (Geeraerts 2010, 82 ff.), constitute a precondition for semantic change. However, even though these relations can be organized hierarchically (e.g., hypo- and hyperonyms), they are not necessarily indicators of the direction of semantic change, which is more complex and unpredictable. The problem of directionality and regularity of semantic change touches upon the centurylong discussion on validating semantics of a morphonological reconstruction. A dictionary of a reconstructed language (Pokorny 1994, Rix and Kümmel 2001), is typically organized by lemmas of mainly verbal lexical roots with vague meanings, from which a large number of derived lexemes of various meanings are derived. This heterogeneity is an obstacle for a systematic, empirical study on directionality and regularity of lexical change (Haspelmath 2004, 26–27). Many factors potentially affect the direction of semantic change, such as language contact (e.g., borrowing) and sociocultural change. Attempts to systematize directionality based on larger data sets are unfortunately still scarce (cf. Urban 2014, 381–383), but colexification and semantic change are important and valuable metrics for identifying concepts’ sociocultural and environmental salience (Epps 2014). In our study, as we will see later on, colexification and meaning change are fundamental for evaluating and classifying lexical concepts (6.3.3). In comparative linguistics, there are controversies surrounding how to validate etymology for classification. In phonology and morphology, shared innovation is viewed as an indicator of sub-classification, and, vice versa, non-shared retention is used as an argument in favor of establishing outgroups, e.g., languages or branches that derive immediately to the root of a family tree (cf. Ringe, Warnow, and Taylor 2002). With lexical change, this validation of shared innovations is more complex, because of the problems of establishing the direction of semantic change and evaluating lexical archaisms. Phylogenetics solves the problem of lexical classification according to the principles outlined by lexicostatistics in the 1950s. The methodological basis is a lexical meaning or concept, a semantic prototype slot, which is filled with the “common, everyday equivalent” (Swadesh 1955, 122) for this meaning in a language. In comparative linguistics, loans are sorted out by relative chronology and sound correspondences; in lexicostatistics, data sets aim to target concepts of low borrowability to avoid the risk of false cognates (i.e., loans) (Tadmor and Haspelmath 2010). Lexemes in lexicostatistical data sets are coded for cognacy, which can be measured for lexical substitution (Dunn 2014, 199 ff.). Here, the comparative and lexicostatistical methods differ: in comparative reconstruction, both etymological subclades and semantic changes of words are of

3.4 Lexicon: classification, reconstruction and principles of change

21

importance to reconstruction and classification. Lexicostatistics accounts for semantic variation and change solely with respect to core meaning gain vs. loss (by inclusion vs. exclusion in data sets), and etymological subclades (e.g., by morphological derivation) are not accounted for. Further, there is a difference in the definition of a cognate. In the comparative method, the reconstruction of morphological derivation is an important part of securing etymologies. In lexicostatistics, the issue of distinguishing cognate traits, e.g., perfect etymological matches, from root-meaning traits, i.e., cognates derived from a common root, is not done systematically (Chang et al. 2015, 201 ff.). This means that in lexicostatistics, shared innovation by morphological derivation is not an issue of establishing subclades; only meaning gain and loss are (see 6.1.2). The basic method of data organization, as proposed by the lexicostatistics in the 1950s, has not changed in the era of Bayesian phylogenetics: the models, methods, and programs for analyzing data has changed, using character-based models with either, 1. maximum parsimony, which aims at finding a tree with the minimum number of evolutionary changes, 2. maximum likelihood/Bayesian analysis, which aims at finding Bayesian estimates for the probability of each tree and produce a probability distribution. In current phylogenetics, the second method is preferred (Dunn 2014). However, despite these discrepancies between methods and the general critique directed towards lexicostatistics and phylogenetics (Hoijer 1956, McMahon et al. 2005, Pereltsvaig and Lewis 2015), lexicostatistical data with basic vocabulary are capable of producing stable and reliable trees, networks or other visualizations, which often correspond to trees generated by the comparative method, at least for languages where comparative method is applicable (cf. Ringe, Warnow, and Taylor 2002). Trees produced by basic vocabulary data and organized according to a lexicostatistical model are useful as reference trees for tests of rate evolution and change of various features, such as typology. The phylogenetic tree in fig. 3 is based on basic vocabulary data for Indo-European languages from the DiACL database. The data includes polymorphism (lexical synonyms) and has a few missing languages in the taxa, which yields a higher root age (≈ 1,000 y) for the maximum clade credibility (MCC) tree than, e.g., (Chang et al. 2015). The program uses ancestry-constraints, which yields a lower root age (1,000 y) for the MCC tree than, e.g., (Bouckaert et al. 2012). To sum up, the issue of semantic change of concepts is vital to classification and reconstruction, both in lexicostatistics and in the comparative method. In lexicostatistics, semantic change disqualifies a lexeme from its prototype slot, and this method has proved to be useful if applied to cognitively and culturally very stable concepts, such as kinship terms or body parts. However, as soon as we move over to customized cultural objects, even if they represent artifacts of everyday utility and attested high age, semantic change is vigorous and real; but it operates within culturally constrained domains. This issue will constitute a core of our chapter on lexical change (5).

Figure 3: BEAST densitree, based on basic vocabulary data for Indo-European languages (from DiACL database).

22 3 Language: classification, reconstruction, and principles of change

4 Description of the database Diachronic Atlas of Comparative Linguistics 4.1 Background and aim The database Diachronic Atlas of Comparative Linguistics (DiACL) forms the basis for the current volume. All data in maps, appendices, lists, figures, and so forth, have been extracted from the database. The aim of the database is to fill data sets as far as possible synchronically and diachronically, using predefined, selected feature sets, which can be extracted and analyzed by means of computational methods, both individually and on a larger scale. The database aims at providing data from historical and reconstructed languages as far as possible considering the constraints provided by data access. This basic aim is an important prerequisite both for the selection of targeted features, and the database design. The targeted data in the database is equivalent to data types that are frequently used in other databases for the purpose of computational cladistic research, i.e., lexical data (basic and culture vocabulary), and typological data (word order, alignment, nominal/verbal morphology). The database design and the character coding have the aim of targeting data sets that have a high granularity in character coding. Furthermore, data sets are pre-prepared for computational analysis, which means that they are filled to a satisfactory level. As far as possible, data sets contain historical and reconstructed data, implementing the comparative method.

4.2 Rationale The rationale of the DiACL database follows a principle of providing data sets which reflect, with a high degree of granularity and accuracy, retained wisdom from comparative-historical linguistics. The underlying aim is to adapt comparative-historical linguistics to computational methods of analyzing data by means of a method of data character coding that encapsulates historical-comparative information. This concerns, e.g., geographic position and temporal extent in prehistory, or known prehistoric language contact, e.g., by lexical borrowing. The theoretical model, underlying the rationale of the database, is a digitization of a spacetime model (cf. 2.2). In implementing the model, the database uses Language (not dialect) as a unique identifier, and this concept includes contemporary, historical, as well as reconstructed languages. By necessity, Languages are definable units, which are constrained in time and space, but with a varying degree of certainty. Therefore, the unique identifier Language is connected to metadata information that includes time period, spatial extent (focal points/polygons), position in a cladistic reference tree, and reliability (modern language/dead language (well documented)/ dead language (fragmentary)/reconstructed language). All this information is retrieved by conventional methods and are sourced in scientific literature. The unique identifier Language links to linguistic data. Feature organization and data character coding is implemented according to a hierarchical model of increasing granularity, which is implemented both in lexical and typological data.

4.3 Language areas and languages The data of the DiACL database is divided into macro-areas, defined as Focus areas. The current atlas only contains data from the focus area Eurasia. The most important family, with the largest data coverage and granularity both synchronically and diachronically, is the Indo-European family of Eurasia, since Indo-European has the richest availability and reliability when it comes to https://doi.org/10.1515/9783110367416-004

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4 Description of the database Diachronic Atlas of Comparative Linguistics

comparative linguistic and historical sources. The Indo-European family has served as a model when the principles of database design and data character coding have been developed. For the other families, only a limited number of extinct languages are present, due to limited availability.

4.4 Data types and design policies The DiACL database contains four main types of data, representing four subsections of the database (fig. 4): 1. Language metadata (including geographic position, temporal extension, reliability, and family tree topology); 2. Lexical and etymological data, including Swadesh lists and culture vocabularies; 3. Typological/morphosyntactic data, including word order, alignment, nominal morphology, and verbal morphology; 4. Source data, including literary sources, unpublished data, and consultants (native speakers). The model of the DiACL database is to organize data sets into functionally hierarchical categories, the purpose of which is as follows: 1. To level out possible redundant polymorphism and create informative, dynamic, and representative data sets of high granularity; 2. To enable partition of data sets on the functional side, in order to test language-internal differences systematically; 3. To create data sets that are representative, symmetrical, controlled, and with a high degree of completeness. The basic model of the database, both for typological and lexical data, aims at a hierarchical organization at the functional side, where the top level is more general (“universal”), whereas lower levels are adapted to an observed reality of a so-called Focus area, which represents a predefined, cohesive macro-area of languages (see map 1). Focus areas have different data sets for both lexical and typological data, with the exception of basic vocabulary (Swadesh list), which is the same for all languages and therefore not distinguished by focus area. Only Eurasia is included in this volume.

4.5 Database structure: tables and relations The core of the database is the entity Language, which contains languages along with attributes, to which all other sections of the database link. Language includes contemporary languages, extinct languages, and reconstructed language states (e.g., Proto-Indo-European, Proto-Kartvelian). Four tables constitute the extended core of the database (cf. fig. 4): – Language, with languages and language metadata – Language tree, which defines the position of languages in a family tree – Focus area, which defines the geographic macro-area – Geographical presence, which defines the geographical presence, by focal point or polygon The table Language contains the metadata information focal point (point on a map), polygon, area, focus area, reliability, and time frame. Outside of the core, the database has three subsections: 1. Lexicology, 2. Typology, and 3. Source. The organization of the subsections typology and lexicology are described under 5.1 and 6.1.

4.5 Database structure: tables and relations

Typological Grid: Name Description Focus Area Focus Area: Name Focal point

LLanguage Tree

Word List: Name Focus Area

Typological Feature: Name Description

Language: Name Focal point P l Polygon Area Focus-area Reliability Time Frame

Word List Category: Name Word List Item: Name

Lexeme For Word List Item

Lexeme: Transcription Script Form IPA Meaning Meaning Note Grammatical Data Lexeme Note

Typological Variant Variant: Name Description

Geographical Presence: Time Frame Polygon (full) Polygon (reduced)

25

Typological Variant Value: Value Note Example

Typological Variant Value Source

Source: Citation Key Full citation

Geographical Presence Source

Lexeme Source

Etymology Source

Etymology: Reliability Note

4.5.1 Language metadata: time, space and family tree topology Language metadata on the table Language includes a standardized name, ISO 693-3 code, alternative names, location, time frame, language area, and reliability (fig. 4). Location gives a focal point, which renders the most proto-typical geographic center for a Language. In the database, the focal point typically is centered within the area where the standard variety of a language is spoken. For some languages, areas are slightly adjusted to avoid overlapping when languages of different time periods are viewed on maps. Alternative names gives various names of the language in different descriptions or in different languages. Time frame gives an estimation of the period within which a language is spoken. These dates are not based on specific historical events; they are rather estimations, given in 50–100-year intervals. Language area is a more detailed classification of language areas, compared to Focus area (see below). Reliability has four distinctions: modern language, dead (well attested), dead (fragmentary), and reconstructed. Dead (well attested) targets languages with corpora large enough to provide data equivalent to living languages, whereas dead (fragmentary) targets languages with lesser documentation: for these languages, data sets have to be controlled for completeness. Reconstructed targets languages without literary sources: they are entirely based on reconstruction by the comparative method. Reconstructed languages contain no typological/morphosyntactic data. They may contain lexical data, but always provided with an *, marking that the forms are reconstructed, not attested. Focus area is a main distinction, separating subsets of data in the database. These Focus areas are macro-areas, to which data sets are adapted. Languages are also classified by language tree (appendix 1b), which defines the position of languages in a tree topology, which basically follows the family tree structure by Glottolog (Hammarström, Forkel, and Haspelmath 2017). In these trees, proto-languages have their own ID and metadata, and are located at nodes within the trees (this is different from Glottolog, which does not have proto-languages as languages).

Etymology Reliability: Description

Note

Figure 4: Tables and relations in the database DiACL. Different coulours represent various subsections of the database. Arrows indicate relations between tables they show the direction of links inside the infrastructure. Red: subsection language and language metadata; blue: subsection typology/morphosyntax; brown: subsection sources; green: subsection lexicon. Tables and categories are described more carefully in the text.

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4 Description of the database Diachronic Atlas of Comparative Linguistics

The database constitutes the basic resource for all data amassed and analyzed in the current volume. For that purpose, we will describe the organization of the respective sections Grammar and Lexicon under the respective sections of this volume (5 and 6).

5 Atlas: Grammar 5.1 Grammar: feature organization and coding 5.1.1 Description of the model for organizing features With grammar data, we have used a hierarchical model for typological/morphosyntactic feature coding. A basic aim is to create data sets fulfilling the requirements of phylogenetic analysis, which means that they should be symmetrical, commensurable, and complete. Like other similar databases, e.g., WALS (Dryer and Haspelmath 2013) or AUTOTYP (Bickel and Nichols 2002a), data sets are based on comparative concepts (Haspelmath 2010), which in the current data set have been adapted to the geographic area Eurasia, including the families Indo-European, Uralic, Turkic, Nakh-Dagestanian, Northwest Caucasian, Kartvelian, and Basque. We use a hierarchical model of feature design, equivalent to the multivariate (Bickel 2007) or micro-variate (Round 2013) models, with four levels of comparative concepts of increasing granularity, where the lowest level is binary (fig. 5). We define a main typological domain, labeled Grid (e.g., ‘word order’), generally corresponding to chapters of WALS (Dryer and Haspelmath 2013), which we divide into Features, (e.g., ‘main clause word order’), which we in turn define by Variants (e.g., ‘SOV’, ‘VSO’), which can be coded by values, either 1 (present), 0 (absent), or NA (no answer). An important part of the feature design is to define basic patterns (e.g., of alignment, agreement, word order), which we use as a matrix, testing against various grammatical aspects of language (e.g., clause structure, tense, word class of core arguments). At the lowest level, Features come out as a string of binary numbers (variant codes) in a language. These strings typically represent property generalizations such as ‘active’, ‘ergative’, ‘agglutinating’, ‘fusional’, ‘left-branching’, or alike. Compared to property generalizations (e.g., as in WALS), the strings of binary values are more suitable for computational analysis, since they allow a measure of patterns with a higher degree of granularity. In language maps or other visualizations, properties are defined as state combinations of feature values, representing generalizations (e.g., of WALS), but with a higher degree of granularity, and also typically, as we will see further on, a higher amount of property generalizations for a specific feature. We will describe and evaluate the model in further detail below, under the chapter for each grammatical domain and in the grammar discussion chapter (5.8). In our model, we have also tried to consider the problem of dependencies between variables (Longobardi et al. 2013, Maddison 1993), which we implement in the hierarchy. Ideally, logical dependencies (A is a prerequisite for B, B is dependent on A) are implemented along the hierarchy, to avoid collision, whereas functional dependencies (A and B share grammatical properties), such as overt marking across grammatical categories are implemented crossing over the branches of the hierarchies, to allow systematic testing of dependencies (fig. 5) (Carling, Larsson, et al. 2018).

1/0 1/0

Grid

Feature Variant

1/0

V i Variant

1/0 /

Variant

1/0 /

Feature

LOGICAL DEPENDENCIES

https://doi.org/10.1515/9783110367416-005

FUN NCTIONAL DEPENDEN NCIES

Variant

Figure 5: Graph illustrating the feature-hierarchical model of grammar data, used in the database. From (Carling, Larsson, et al. 2018).

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5 Atlas: Grammar

A further issue is the selection of features for comparison. Here, it is possible to apply a position from a bird’s eye overview to a very detailed level of local adaptation and granularity. Standards are set through data sets such as WALS (Dryer and Haspelmath 2013), SAILS (Muysken et al. 2014), AUTOTYP (Bickel and Nichols 2002b) or EUROTYP (Eurotyp 1998).

5.1.2 Grammar data set: basic principles of selection of features In the data set, which is the basis for the grammar parts of this atlas, we target a continuous language area with a known long history of linguistic records and a rich diversity and variation. The data set has two dimensions of restriction: an areal dimension (e.g., the coverage of a specific geographic area, see map 2a–c), and a temporal dimension (from present time to the earliest textual attestations). We have selected the grammar domains of alignment, nominal morphology, tense, verbal morphology, and word order (table 1). Here, we select features and variants known to be of significance for the area in synchrony (Dryer and Haspelmath 2013, Kortmann and Auwera 2011, Nichols 1998), but to constrain features and variants with respect to diachrony, so that we can populate the dataset with data from ancient languages. We have used a combined matrix and questionnaire of feature variants for filling data from grammars as well as from fieldwork (appendix 2a). For historical doculects, we have used reliable grammatical descriptions, for modern languages, we have used grammatical descriptions as well

Tab. 1: Overview of domains and features of the dataset visualized by maps in this atlas (for a complete list of feature in the database DiACL, including questionnaire and ID, see appendix 2a). Domain (Grid)

Feature

Alignment

Alignment by Nouns in Present Progressive Alignment by Nouns in Simple Past Alignment by Pronouns in Present Progressive Alignment by Pronouns in Simple Past

Nominal morphology

Realization of case marking in a Noun Phrase Definiteness marking Gender and Noun class marking Nominal case system Pronominal case system

Tense

Future tense marking

Verbal morphology

Agreement with respect to Agent (A) in Present Progressive Agreement with respect to Dative in Present Progressive Agreement with respect to Object in Present Progressive Agreement with respect to Agent in Simple Past Agreement with respect to Object in Simple Past

Word order

Word order Clitic Pronoun – Finite Verb (Predicate) Word order Clitic Pronoun – Infinitive Verb Word order Clitic Pronoun – Participle Verb Word order Object – Infinitive Word order in Main Clauses Word order Subordinate Clause Word order Noun – Relative clause Word order Noun – Possessor (Genitive) Word order Noun − Adjective Word order Object − Participle Word order Adposition − Noun Position of Question word

5.1 Grammar: feature organization and coding

29

Tab. 2: Number and type of languages with grammar data in this volume. For a complete list, see appendix 2c. Family

Type

Time frame

Number

Indo-European

Archaic Ancient Medieval Modern Romani Modern Modern Modern Modern Medieval Modern Modern

−2000 −  −500  −500 −  +500  +500 − +1500 +1500 − +2000 +1500 − +2000 +1500 − +2000 +1500 − +2000 +1500 − +2000 +1500 − +2000  +500 − +1500 +1500 − +2000 +1500 − +2000

  3   5  29  79  10   4   6   4   1   1   4   2

Uralic Turkic Nakh-Dagestanian NW Caucasian Kartvelian Basque TOTAL

148

as language consultants (appendix 4a–b). The dataset includes languages from seven families (Indo-European, Uralic, Nakh-Dagestanian, Northwest Caucasian, Kartvelian, Turkic, Basque), and, as far as possible, earlier states of contemporary languages, dead branches, as well as later stages of migrated languages, from the earliest sources up to the modern period. We include as many dialects/languages as possible from the Indo-Aryan group Romani, including also mixed varieties (map 2a–c, table 2, appendix 1). Romani dialects, which represent a migration from Central India to Europe around 1,500 years BP, and which belong to the Indo-Aryan branch, will be visualized on separate maps, in order to avoid unnecessary confusion with surrounding languages.

5.1.3 Coding policies To begin, we identify a few basic problems that we assume will affect the outcome of the coding on a larger basis. Some of these depend on the presence of contemporary and ancient languages in the data set, others depend on policy of defining properties: 1. How do we code features so that the strings of 1 and 0 become representative and commensurable between languages of different families and languages of different time periods? 2. How do we deal with an ongoing change within an attested language state? 3. How do we deal with polymorphism (within languages) as well as uncertainty of property coding (e.g., in ancient languages)? We have used a policy aiming at a maximal symmetry of 1 and 0 for features. The coding method enables, in case of a feature with two variants, the following options: 1/0, 0/1, 1/1, 0/0, or NA (for one or both variants). In the case of uncertainty or possible polymorphic behavior, we have adapted the following policy for coding: 1. 1/0, 0/1: A natural, dominating behavior of a feature (e.g., word order SOV or SVO) can be identified. A recurrent problem is that the decision can be hard to make, in particular when there is an ongoing change or there are available corpora giving statistical information about the feature’s behavior and the domination of the one or other behavior is not entirely obvious. Here, we define the coding by frequency (see 5.6). This coding is also used to define a default property of a paradigm (e.g., in verbal conjugation or case systems). However, here there may be differences within a grammatical category, e.g., between genders in a case system, between numbers in verbal morphology etc., where we select the default category,

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which in our model is represented by the semantically and morphologically unmarked category in languages, e.g., non-definite, non-animate. 2. 1/1: The language possesses polymorphic behavior and no natural, dominant behavior can be identified (e.g., a language has both SOV and SOV). A problem is that this definition is often problematic and hard to make in an individual language (cf. previous point). 3. 0/0: This coding means that the targeted feature is impossible or non-existent in the language. As an example, we might think of infinitive word order in a language that does not possess a morphological infinitive. 4. NA: This type of coding means that the category might exist (cf. previous point), but we do not have enough knowledge about its behavior to code either 1 or 0. In the following chapters, we will look more in detail at the implications of the coding patterns for selected features. The compilation of a data set with features of both contemporary and ancient languages constitutes a great challenge. Our aim is to make differences between 1 and 0 meaningful for both computational analysis of clusterings of languages, mapping of value combinations, analysis of change, i.e., gains (0 → 1) and losses (1 → 0) in the data, as well as analysis of evolutionary patterns in the data sets (Cathcart et al. 2018). An important issue is to avoid lacunae in the data, a relevant problem to ancient, literary languages. Therefore, we have adapted our data set to focus on features that are extractable from grammars or corpora of ancient languages, as well as adapted the number of languages by excluding ancient languages with a low level of data coverage.

5.1.4 Motivation for our selection of features The current chapter has sketched the general principles behind the coding system used in the grammatical data set, which forms the basis for the map visualizations in chapter 5. The coding system represents generalizations about grammar, i.e., typological and morphosyntactic features, as a combination of 1/0 or NA, which form the basis for computational analyses or hypothesis testing. In our data set, there is a large amount of variation in the occurring combinations, but the variation is not endless, and it reflects the reality of typological variation and diversity over the area. Our grammatical data embraces five domains of grammar: word order, nominal morphology, verbal morphology, tense, and alignment. These domains have been chosen due to their frequent occurrence in typological literature and their presumed internal correlation (Nichols 1992), as well as their presumed structural stability and tendency to indicate large-scale and extensive temporal and areal trends of change (Nichols 1995, Dediu and Cysouw 2013). We have, as elsewhere in this volume, selected to include data from ancient languages as far as possible and the applications, results, and visualizations of chapter 5 therefore reflect a change spanning more than 3,700 years. In general, features or variants are meaningful first when they are seen as dependent, i.e., as combinations of features or as identified according to their inherent functioning in language. They are also meaningful when seen in contrast or clumped together in groups, which will be an important issue in the visualizations of chapter 5.

5.2 Grammar visualizations: aim and models The grammatical data of DiACL may be used for evolutionary investigations, reconstructing (gain and loss) change rates and applying models for measuring areality and evolutionary behavior, where ancient data can be used to verify reconstructions (Cathcart et al. 2018). In this section,

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we will visualize geographically the spread of the various grammar properties, as well as the distribution of various clusters of features and variants, organized according to their grammatical classification (morphology, syntax, word class). A summary of results from an evolutionary reconstruction model will be discussed in 5.7.2. Our data set embraces four important domains of grammar from a typological perspective: Alignment, i.e., the typological profile of the organization of the core (A,S,O) in languages, Nominal morphology, i.e., the structure and profile of grammar properties of the Noun Phrase, Verbal morphology, i.e., the structure, profile, and categories involved in conjugation of verbal categories in languages, and finally Word order, i.e., the typological profile of languages of positions and order or constituents in syntax. In the atlas, we visualize the data by two types of maps: feature maps and cluster maps. Feature maps (5.3–5.6) visualize occurring state combinations of variants in the data. The combinations consist of a string of values (1,0) for a variant, according to our hierarchical model (fig. 5). These represent different property generalizations of languages, which we will describe more carefully in chapters 5.3–5.6 below. Languages with missing data (NA) for a variant in the state combinations are left out in the visualizations (i.e., we erase all values for the state combination). A complete list of domains, features, and attested combinations of the database is given in appendix 2a. The state combinations used in the current atlas are given in appendix 2b (by feature) and 2c (by language). Two of our features (see table 8 and 10), the properties Nominal morphology and Pronominal morphology (in the original setup used in the database) result in an unmanageable amount of state combinations, which would render a visualization meaningless. Therefore, state combinations with these two features have been simplified (this simplification process is described under 5.4.1). Further, not all state combinations of the data in DiACL are visualized by maps in the atlas. We have made a selection of the most important and characteristic properties, where the mapped state combinations give interesting and clear patterns, which aim at demonstrating and explaining the complexity and diversity of various features within the macro-area. Domains (Grids), features (Features) and state combinations (combinations of Variants) used in the atlas are given in appendix 2b–c. In a second set of visualizations, we will analyze how grammatical features cluster in relation to their areal distribution. The basic aim of these mappings is to investigate traces of contact in prehistory by means of clustering and mapping the grammar data. The method, model and analysis are described more carefully in 5.7–5.8. Chapter 5.8 discusses the results of grammar visualizations, both for state combination maps, cluster maps, and reconstructions.

5.3 Alignment Beginning with alignment, we have a scenario where we want the coding to reflect a complex diversity both in synchrony and diachrony. Coding of alignment refers to properties of grammatical relations and how languages mark S (Subject), A (Agent), and O (Object). There are several available systems that could be used for defining an alignment matrix, both theoretically (Bickel 2011a, Dixon 2010a, 1994), as well as by definitions in other databases, e.g., WALS or AUTOTYP (Dryer and Haspelmath 2013, Bickel and Nichols 2002a). We have, also accounting for the diachronic dimension (Bauer 2000), selected a model that aims at describing various aspects of accusative, active, and ergative marking, starting from the core arguments. We define four correlations, A=O, A=Sa, O=So, and Sa=So (Dixon 2010b, 126 ff.), for describing the coding relations of A (Agent, first argument of transitive predicates), S (Subject, first argument of intransitive predicates), and O (Object, second argument of transitive predicates) with verbs of various transitivity (intransitive, transitive) or semantic (active/stative) types (Sa/So) (see table 3). These correlations are tested for differences in marking related to the word class of the first argument (noun/ pronoun) and the tense of the verbal predicate (present progressive/past tense) (table 4). A sec-

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Tab. 3: Basic type correlations for alignment systems and evaluation of the outcome. Variant

Description (for marking of A, S, and O)

A=O?

The agent (A) of a transitive verb bears the same marking as the subject (O) of a transitive verb.

A=Sa

The agent (A) of a transitive-active verb bears the same marking as the subject (S) of an intransitive-active verb.

Sa=So

The subject (S) of an intransitive-active verb bears the same marking as the subject (S) of an intransitive-stative verb.

So=O

The subject (S) of an intransitive-stative verb bears the same marking as the object (O) of a transitive-active verb.

Tab. 4: Model for coding of basic alignment types (by a matrix of properties) against word class of the first argument and tense of the predicate. Matrix

with

A=O? A=Sa? O=So? Sa=So?

Word class of first argument

in

Noun Pronoun

Tense Present progressive Simple past

Tab. 5: List of features of the grid Alignment (appendix 2a). Feature

Explanation

Compare PROG-PAST

What is the marking relation between subject and object in present progressive and simple past?

Noun: Present progressive

In present progressive: how is the marking of subject and object of nouns realized?

Noun: Simple past

In simple past: how is the marking of subject and object of nouns realized?

Pronoun: Present progressive

In present progressive: how is the marking of subject and object of pronouns realized?

Pronoun: Simple past

In present progressive: how is the marking of subject and object of pronouns realized?

Reflexive pronoun in transitive clause

What is the alignment of reflexive pronouns?

Verb: Present progressive

In present progressive, how is alignment realized on the verb?

Verb: Simple past

In simple past, how is alignment realized on the verb?

ond coding variant tests alignment properties with verbs, targeting marking differences in verbal agreement with reference to S, A, and O (table 5). The state combinations of 1 and 0, representing different alignment types, such as accusative, tripartite, ergative, active, or no case marking for an individual feature then come out different in individual languages, depending on deviations due to word class of the first argument, and tense of the verbal core. Table 6 gives an overview of how this divergence comes out in various languages for the feature Noun: Present progressive. The feature captures how alignment is coded on nouns in present progressive tense, with 5 possible state combinations present in the data. The pattern 1/1/1/1 (table 6, type b), found in, among others, Swedish and French, implies that the language has no alignment coding (example 2). Nominative-accusative coding, as in Sanskrit, Gothic, Latin, Icelandic etc, is very frequent in the data, in particular among the

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Tab. 6: Samples of state combinations (i.e., existing combinations of 1/0, see 5.1.1) for the alignment feature Noun: Present Progressive (see maps 3a–c). Type

A=O?

A=Sa?

O=So?

Sa=So?

Sample of languages (not complete list)

Alignment type

a)

0

1

0

1

b) c) d) e)

1 0 0 0

1 0 0 1

1 0 1 1

1 1 1 0

Sanskrit, Gothic, Latin, Irish, Icelandic, Tocharian, Lithuanian, Luwian Swedish, Basque, French, Kurdish, Breton Nepali, Assamese Kabardian, Kryz, Khwarshi Laz, Lezgian

nominativeaccusative no case marking tripartite ergative active

ancient languages (example 1). Tripartite, ergative, and active codings occur as well. Karbadian (East Circassian) can be used to illustrate d), ergative case marking (example 3). An example of coding type e), active alignment, with split in the marking of intransitive subjects, nominative and ergative, is present in Laz (example 4). Here, case marking patterns do not differ according to tense/aspect, which is the case in, e.g. Georgian. Tocharian B, coding type a), nominative-accusative (1)

ṣāmani aśiyanaṃts pelaikne aksaske-ṃ monk.nom.pl nun.gen.pl Law.obl.sg teach.3pl.prs-cl.3pl ‘the monks teach the Law to the nuns’ (PK.AS.18B a4)

Swedish, coding type b), no alignment, with noun, present progressive (2)

flick-an klapp-ar en hund girl-def.sg pat-prs.3sg indf dog ‘the girl pats a dog’

Circassian, coding type d), ergative (Kumakhov and Vamling 2009, 34, 80–82, 152) (3)

a. He-r ø-š'ə-ɬə-ø dog-abs s3sg-loc-lie-prs ‘The dog is lying’ b. Q’ardenə-r ma-že-ø Kardan-abs s3sg-run-prs ‘Kardan is running’ c. Ljenske-m tχəɬə-r ø-je-tχ-ø Lensky-erg book-abs o3sg-s3sg-write-prs ‘Lensky is writing the book’ d. Ljenske-r me-laz'e-ø Lensky-abs s3sg-work-prs ‘Lensky is working’ e Fəzə-m blənə-r ø-je-le-ø woman-erg wall-abs o3sg-s3sg-paint-prs ‘The woman is painting the wall’ f. Fəzə-r ma-le-ø woman-abs s3sg-paint-prs ‘The woman is painting (engaged in painting)’

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Laz, Coding type e), active (p.c. Omar Memishishi) (Holisky 1991, 446) (4)

a. bere-k ǯoɣori-s kual-i meču child-erg dog-dat bread-nom give.aor ‘The child gave bread to the dog’ b. bere-k imgars child-erg cry.3sg.prs ‘The child cries’ c. bere gondunun child.nom get.lost.fut ‘The child will get lost’

The alignment state combinations that occur in our data (appendix 2c), representing the five different alignment systems: no marking, accusative, ergative, active, and tripartite are visualized with a noun as first argument in present progressive (maps 3a–c), with a noun as first argument in simple past (maps 4a–c), with a pronoun as first argument in present progressive (maps 5a–c), with a pronoun as first argument in simple past (maps 6a–c). State combinations in languages are found in appendix 2b–c; evaluations are found in chapter 5.8.

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Map 3a: Alignment by Nouns in Present Progressive (modern).

5.3 Alignment

37

Map 3b: Alignment by Nouns in Present Progressive (historical).

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5.3 Alignment

Map 3c: Alignment by Nouns in Present Progressive (Romani).

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Map 4a: Alignment by Nouns in Simple Past (modern).

5.3 Alignment

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Map 4b: Alignment by Nouns in Simple Past (historical).

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5.3 Alignment

Map 4c: Alignment by Nouns in Simple Past (Romani).

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Map 5a: Alignment by Pronouns in Present Progressive (modern).

5.3 Alignment

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Map 5b: Alignment by Pronouns in Present Progressive (historical).

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5.3 Alignment

Map 5c: Alignment by Pronouns in Present Progressive (Romani).

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Map 6a: Alignment by Pronouns in Simple Past (modern).

5.3 Alignment

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Map 6b: Alignment by Pronouns in Simple Past (historical).

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5.4 Nominal morphology

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5.4 Nominal morphology The domain Nominal morphology targets nominal and pronominal case, gender, number, noun class distinctions, definiteness, and gender and preposition agreement (table 7). The selection of features and variants aim at capturing the diversity of the area with respect to morphological patterns of nouns and pronouns. We will deal with this domain under four headings, Case (5.4.1), Gender and noun class (5.4.2), Prepositional agreement (5.4.3) and Definiteness (5.4.4). Tab. 7: Grid Nominal morphology: features, occurring variants (V), attested combinations of 1 and 0 (C), and explanation (appendix 2a). FEATURE

V

C

EXPLANATION

Nominal case Pronominal case Case marking Gender/ Noun class Definiteness marking Gender agreement Preposition agreement

9 7 5 4 5 1 1

47 20  9  9 13  2  2

Organization and morphological type of nominal cases Organization and morphological type of pronominal cases Elements of NP with obligatory case marking Gender / noun class distinctions Elements of NP with definiteness marking Gender agreement on the adjective Occurrence of preposition agreement

5.4.1 Case To begin with, we consider the feature Nominal morphology: Nominal case. The feature has 9 feature variants (table 8). Of the variants, 7 target type and number of cases, aiming at describing the extension of the case system. Beyond that, the two variants AGGL.CASE.NR and AGGL.CASE aim at capturing the typological profile of the architectural design of the case system. In Eurasian languages, belonging to Indo-European, Turkish, Uralic, Kartvelian, Nakh-Dagestanian and Northwest Caucasian families, there are several distinct types of case systems, ranging from isolating over fusional to agglutinating, and with several systems which represent mixtures between these states. In the data set, the values AGGL.CASE.NR and AGGL.CASE with the possible variants 1/1, 1/0, and 0/0 (table 9), aim at capturing the typological profile of the

Map 6c: Alignment by Pronouns in Simple Past (Romani).

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Tab. 8: Overview of variants of the feature Nominal morphology / Nominal case (note that the order of variants is alphabetical), with reference to example and ID (appendix 2a). VARIANT

QUESTIONNAIRE (y/n = 1/0)

ID

> 7 Cases

Are there more than 7 cases?

250

AGGL.CASE.NR

Are plural cases formed by combining a plural affix and a case affix in an agglutinative manner?

252

AGGL.CASE

Are there any cases which are visibly agglutinative, i.e., built up by several distinct, segmentable affixes?

251

DAT

Is there a specific case form for the recipient, which is different from the case form of, e.g., the object? (E.g. The man gives a book (O) to the child (DAT))

245

GEN

Is there a special case form to express genitive, which is different from the agent/object case?

246

GEN/DAT

Is there a special noun form to express genitive, which is not the the same as dative (recipient) case?

247

OBL-Cases

Are there any cases besides agent, object, genitive, dative, and vocative? (E.g., local cases)

249

O-case

Are there different noun forms for agent and object case? (English: 0 (no cases) Russian: 1 (different noun forms for accusative and nominative) Basque: 1 (different noun forms for ergative and absolutive)

244

VOC

Is there a special noun form to express vocative which is not the same as agent or object case?

248

Tab. 9: Sample of state combinations for the feature Nominal morphology / Nominal case in Swedish, Classical Greek, Tocharian A, Turkish, and Romani (Sinte) (for a complete list of coding patterns see appendix 2b–c). VARIANT

Swedish

Classical Greek

Tocharian A

Turkish

Romani (Sinte)

> 7 Cases AGGL.CASE.NR AGGL.CASE DAT GEN GEN/DAT OBL-Cases O-case VOC

0 0 0 0 0 0 0 0 0

0 0 0 1 1 1 0 1 1

1 1 1 0 1 0 1 1 0

0 1 1 1 1 1 1 1 0

1 1 1 1 1 1 1 1 1

paradigm. For typological classifications of case systems we have the aspects of segmentability, i.e., the ability in synchrony to segment morphemes in case forms; concatenativity, i.e., the rules of language to align morphemes with respect to each other (Haspelmath and Sims 2013, 34 ff., Bickel and Nichols 2007, 181–182); and exponence, i.e., the density of features and values of morphemes (Haspelmath and Sims 2013, 82 ff., Bickel and Nichols 2007, 188). Generally, agglutinating case systems are segmented, concatenative, and display a separative exponence (i.e., features/values, such as case, number, and gender, are distributed over morphemes), whereas fusional case systems are less clearly segmented, non-concatenative, and display non-separative exponence. In our definition, the variant AGGL.CASE.NR (“Are plural cases formed by combining an (infixed) plural affix and case affix in an agglutinative manner?”) targets the way in which the distinction of number is built up in case systems. If the distinction is segmented and concatenative with respect to case, e.g., by means of infixation or base allomorphy, then the answer to this question is yes (1). If number distinction is integrated and cumulative with case, then the answer is no (0). The variant AGGL.CASE (“Are there cases which are visibly agglutinative, i.e., built up by several distinct, segmentable affixes?”) targets the typological profile of case. If most or sever-

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Tab. 10: Variants of the feature Nominal morphology: Pronominal case with ID (appendix 2a). FEATURE

QUESTIONNAIRE (y/n = 1/0)

ID

> 7 Cases

Are there more than 7 cases?

250

A≠O

In pronouns, is the marking different for the case of the agent and object?

253

AGGL.CASE

Are plural cases formed by combining an (infixed) plural affix and a case affix in an agglutinative manner?

258

AGGL.CASE.NR

Are there any cases which are visibly agglutinative, i.e., built up by several distinct, segmentable affixes?

259

DAT≠O

In pronouns, is the marking different for the case of the recipient and the object?

254

OBL-Cases

Are there any cases besides agent, object, genitive, dative, and vocative? (E.g., local cases)

256

VOC

Is there a special noun form to express vocative which is not the same as agent or object case?

255

al cases are agglutinating, i.e., they are segmented, concatenative, and have a separative exponence, the answer is yes (1). Otherwise, e.g., if case is cumulative with number or gender, the answer is no (0). In theory, these two features should be able to capture most of the typological diversity of Eurasian languages. There are, however, several instances where this distinction comes up short. The combination 0/0 targets more or less completely fusional systems, such as Classical Greek (example 5a). In this system, there are no or very few traces of segmentable, concatenative coding of case and number, as in Turkish (example 5b). The combination 0/0 also targets casefree languages, such as Swedish. Therefore, as described above, it is important to consider variants in our classification not as independent items, but as dependent feature values. The difference between languages such as Classical Greek and Swedish is mirrored through the combined variants of the feature Nominal case (table 9), and in evolutionary studies, the inherent dependency of features is important in tests, where features should be treated as multistate characters rather than independent variants (Carling, Larsson, et al. 2018, Cathcart et al. 2018, Carling and Cathcart Forthcoming). The combination 1/1, targets typically fully agglutinating systems, such as Turkish (example 5b), with segmented, concatenative morphemes and separative exponence. However, our distinction is not capable of distinguishing an agglutinating system like Turkish from a mixed system of the type that occurs in Tocharian (example 5c), or in Romani, where there is fusional inflection in core cases. Both these types receive the marking 1/1. On the other hand, there are in the database a couple of systems that have the property of forming segmented, concatenative number marking which have non-separative exponence elsewhere in the case system. An example is the complex and archaic system of Luwian (example 5d). The feature Nominal morphology: Pronominal case is similar to Nominal case, but has fewer variants (table 10). Case system of Classical Greek, exemplified on neānías ‘a young man, youth’ (Blomqvist and Jastrup 1991, 41, Rix 1992). (5) a. Nom. Gen. Dat. Acc. Voc.

Sg. neāníās neāníou neānía᷂s neāníān neāníā

Pl. neāníai neāníôn neāníais neāníās

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Case system of Turkish (Göksel and Kerslake 2005, 468) b. Abs. Acc. Gen. Dat. Loc. Abl.

Sg. — -(y)i -(n)in -(y)e -de -den

Pl. -ler -ler-i -ler-in -ler-e -ler-de -ler-den

Case system of Tocharian A, exemplified on A yuk ‘horse’ (Pinault 2008, 468) c. Nom. Obl. Gen. Instr. Perl. Com. All. Abl. Loc.

Sg. yuk yuk yukes yuk-yo yuk-ā yuk-aśśäl yuk-ac yuk-äṣ yuk-aṃ

Pl. yukañ yuk-as yukaśśi yuk-as-yo yuk-as-ā yuk-as-aśśäl yuk-as-ac yuk-as-äṣ yuk-as-aṃ

The case system of Hieroglyphic/ Cuneiform Luwian (Melchert 2003, 186) d. Nom.Anim. Acc.Anim. Voc. Nom.-Acc.Nt. Erg. Gen. Dat.-Loc. Abl.Instr.

Sg. -š -n [-Ø] -Ø, -n -antiš ---, -as, -asi -i -ati

Pl. -nzi -nz(a) Nominative -a, [-Ø] -antinzi ---, -as, -asi -anz(a) -ati

In the corpus, the feature Nominal morphology: Nominal case comes out as no less than 47 different variants, a range that is meaningless to visualize on maps that include only three times as many languages. Therefore, we have been urged to simplify the state combinations to a distinct number of types, targeting the specific features of a case paradigm. The full set of state combinations is found in appendix 2a. Among the variants of Nominal morphology: Nominal case, four types are of importance for describing the case system. First, we have the variants describing the typological profile of the case system, i.e., whether number distinction is marked by agglutination (AGGL.CASE.NR) or whether any agglutinative tendency is found in the system (AGGL.CASE). A value 1 for any of these variants implies presence of agglutination in the case system and may thus be conflated to a property ‘presence of agglutination’. Second, we have the variants marking the presence of genitive and dative, i.e., cases for possessor and recipient, which distinguish whether there is a specific case for the recipient (N.DAT), whether there is a special form for the genitive, which is different from the A/O case (GEN), and whether there is a special form for the genitive, which is different from the dative (GEN/DAT). A value 1 for any of these variants implies that there is a genitive, a dative, or a genitive/dative in the language. Further, we have the variant distinguishing whether the language marks the difference between A/O in the system, targeting both nominative-accusative and ergative languages (O-Case). A value 1 marks the property of core case

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Tab. 11: Simplified state combinations (numbered by order of frequency in the data) for the feature Nominal morphology: Nominal case (for a complete list of the underlying order of variants and the combinations of 1/0, see appendix 2b). Nr.

Description

 1  2  3  4  5  6  7  8  9 10 11 12

No agglutinative tendency, no genitive and/or dative, no A/O distinction, no local cases No agglutinative tendency, no genitive and/or dative, A/O distinction, no local cases No agglutinative tendency, no genitive and/or dative, A/O distinction, local cases No agglutinative tendency, genitive and/or dative, no A/O distinction, no local cases No agglutinative tendency, genitive and/or dative, A/O distinction, no local cases No agglutinative tendency, genitive and/or dative, A/O distinction, local cases Agglutinative tendency, no genitive and/or dative, no A/O distinction, local cases Agglutinative tendency, no genitive and/or dative, A/O distinction, local cases Agglutinative tendency, genitive and/or dative, no A/O distinction, no local cases Agglutinative tendency, genitive and/or dative, A/O distinction, no local cases Agglutinative tendency, genitive and/or dative, A/O distinction, no local cases Agglutinative tendency, genitive and/or dative, A/O distinction, local cases

Tab. 12: Simplified state combinations (numbered by order of frequency in the data) for the feature Nominal morphology: Pronominal case (for a complete list of the underlying order of variants and the combinations of 1/0, see appendix 2b). Nr.

Explanation

 1  2  3  4  5  6  7  8  9 10 11 12

No agglutinative tendency, no A/O distinction, no DAT/O distinction, no local cases No agglutinative tendency, no A/O distinction, no DAT/O distinction, local cases No agglutinative tendency, no A/O distinction, DAT/O distinction, local cases No agglutinative tendency, A/O distinction, no DAT/O distinction, no local cases No agglutinative tendency, A/O distinction, no DAT/O distinction, local cases No agglutinative tendency, A/O distinction, DAT/O distinction, no local cases No agglutinative tendency, A/O distinction, DAT/O distinction, local cases Agglutinative tendency, no A/O distinction, DAT/O distinction, local cases Agglutinative tendency, A/O distinction, no DAT/O distinction, no local cases Agglutinative tendency, A/O distinction, DAT/O distinction, no local cases No agglutinative tendency, no A/O distinction, no DAT/O distinction, no local cases Agglutinative tendency, A/O distinction, DAT/O distinction, local cases

marking. Finally, we have the variant defining whether the language has non-core (e.g., local) cases, which in our definition targets cases besides S, A, O, and case for possessor (genitive), case for recipient (dative), and vocative. In the feature, there are two more variants, whether a language has more than 7 cases (< 7 Cases), and whether the language has a vocative case (VOC). Complete values and state combinations can be found in appendix 2b–c. The feature Pronominal case is similar to Nominal case, but has fewer variants (table 10) and also fewer state combinations, 20 (table 7). Still, it is relevant to simplify these state combinations following the pattern of the feature Nominal case, so that the map visualizations display comparable data. When the state combinations are reduced following the pattern of Nominal case (table 11), 12 different combinations remain (table 12). Next comes the feature Nominal morphology: Case marking, where we distinguish different types of case marking in an NP. The feature falls out as 9 different state combinations in the data (appendix 2b–c, table 13, 14). The feature targets whether case marking is obligatory on the last element of the NP, such as in Basque (example 6a–c) or on the first element of the NP. Further variants involve whether case marking is obligatory on the noun, the adjective, or on the article.

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Tab. 13: Variants of the feature Nominal morphology: Nominal case with ID. VARIANT

DESCRIPTION

ID

CASE-LAST

Is the case marking obligatory on the last element of the NP (i.e., it is only realized once in the NP, even if it consists of several elements)?

260

CASE-FIRST

Is the case marking obligatory on the first element of the NP (i.e., it is only realized once in the NP, even if it consists of several elements)?

259

CASE-N

Is the case marking obligatory on the noun?

254

CASE-ADJ

Is the case marking obligatory on the adjective?

256

CASE-ART

Is the case marking realized on the article?

255

Tab. 14: State combinations (numbered by order of frequency in the data) for the feature Nominal morphology: Case marking (for a complete list of the underlying order of variants and the combinations of 1/0, see appendix 2b). Nr.

Explanation

1 2 3 4 5 6 7 8 9

No case marking Case only on the noun Case obligatory on the last member of the NP Case obligatory on the last member of the NP and case and on the noun Case marking on the article and case on the noun Case marking on the adjective and on the noun Case on the adjective, the last member of the NP, and on the noun Case on the adjective and on the article Case marking in the adjective, on the article, and on the noun

Case on the last element of the NP in Basque (ID260) (Hualde and Ortiz de Urbina 2003, 171) (6)

a. gizon-a-ri man-def-dat ‘to the man’ b. gizon gazte-a-ri man young-def-dat ‘to the young man’ c. gizon gazte hon-i man young this-dat ‘to this young man’

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Map 7a: Gender and Noun class marking (modern).

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Map 7b: Gender and Noun class marking (historical).

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Map 7c: Gender and Noun class marking (Romani).

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Map 8a: Nominal case system (modern).

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Map 8b: Nominal case system (historical).

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Map 8c: Nominal case system (Romani).

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Map 9a: Pronominal case system (modern).

5.4 Nominal morphology

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Map 9b: Pronominal case system (historical).

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Map 9c: Pronominal case system (Romani).

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Map 10a: Realization of case marking in a Noun Phrase (modern).

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Map 10b: Realization of case marking in a Noun Phrase (historical).

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5.4.2 Gender and Noun class Gender marking and gender systems we describe by two different features, Gender / Noun class, and Gender agreement. Gender agreement is defined by one single variant, which targets whether a predicative adjective agrees with the subject of the clause in gender (PRED-ADJ). Gender / Noun class marking (table 15) is distinguished according to whether there are more than 5 noun classes / genders (< 5 GENDER), and whether there is a special noun class for non-human animates realized on an agreeing article, adjective or verb (ANIM). The distinction between masculine and feminine we define by whether there is an obligatory gender distinction realized on an agreeing article, adjective, or verb (M/F). This may be marked either on the adjective, such as in Russian, on both the article and the adjective, such as in German, or on the verb, as in some Nakh-Dagestanian Caucasian languages (example 7a–b). The same definition is used for the neuter marking. Batsbi (Nakh-Dagestanian) has two classes for nouns, denoting male (v-) and female (j-) humans, respectively. Remaining classes are mixed and include other words denoting animates. There is thus not a special noun class for non-human animates, but such nouns trigger agreement: in the example 8, k’uit’I ‘cat’ triggers noun class agreement in the adjective Daqon ‘big’ (but not all adjectives take these markers) (example 8).

Tab. 15: Variants of the feature Nominal morphology: Gender / Noun class. FEATURE

EXPLANATION

ID

< 5 GENDER ANIM

Are there more than 5 noun classes (or genders)? Is there a special noun class for non-human animates realized on an agreeing article, adjective or verb? Is there an obligatory gender distinction between masculine and feminine realized on an agreeing article or adjective? Is there a special neutral gender for nouns realized on an agreeing article, adjective or verb?

268 267

M/F NEUTR

265 266

Map 10c: Realization of case marking in a Noun Phrase (Romani).

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Tab. 16: Assignment to noun classes (taking gender agreement) in Khwarshi (Khalilova 2009, 44–46). Class Noun Noun Noun Noun Noun

Includes class class class class class

1 2 3 4 5

nouns denoting male humans nouns denoting female humans mixed semantics, includes nouns denoting animals (but not the young of animals) abstract notions and liquids the young of animals

Tab. 17: State combinations (numbered by order of frequency) of the feature Nominal morphology: Gender / Noun class (for a complete list of the underlying order of variants and the combinations of 1/0, see appendix 2b). Nr.

EXPLANATION

1 2 3 4 5 6 7 8 9

Masculine – feminine distinction Distinction of a default and a neuter gender Special noun class for non-human animates No gender marking Masculine – feminine – neuter distinction Distinction of masculine, feminine, and noun class of non-human animates Distinction of non-human animate and neuter Distinction of non-human animate, masculine, feminine and neuter More than five genders, including non-human animate, masculine, feminine, and neuter

In Kwarshi (Nakh-Dagestanian), gender/number agreement is found on verbs, adjectives, adverbs, postpositions and demonstrative pronouns (Khalilova 2009, 41). Most adjectives (approx. 60 %) take gender/number agreement, and these markers occur as either prefixes (of Khwarshi origin) or suffixes (of Avar origin) (examples 9–10). In our data, Gender/Noun class variants fall out into 8 state combinations (table 17). Gender marking on the verb in Chechen (Nichols 1994, 37) (7)

a. san vaša a:ra v-e:lira my brother out V-went ‘My brother (human V) went out’ b. san jiša a:ra j-e:lira my sister out J-went ‘My sister (human J) went out’

Non-human animate agreement in Batsbi (8)

ši D-aqon ʕarč’in k’uit’I sen 1sg.gen two IVcl-big black cat ‘my two large black cats’

Gender agreement on adjectives in Khwarshi (Khalilova 2009, 100) (9)

a. ø-ogu obu I-good father(I) ‘good father’

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b. y-ogu kad II-good girl(II) ‘good girl Agreement on the adjective with a non-human animate in Khwarshi (Khalilova 2009, 103) (10) idu soyro b-ogu goli this horse(III) III-good be.prs ‘this horse is good’

5.4.3 Prepositional agreement We investigate prepositional agreement, a property which is typical for the Celtic languages (ID 275, example 11a–b and 12). Prepositional agreement with Object in Welsh (ID275) (Borsley, Tellerman, and Willis 2007, 199) (11) a. arnaf i on.1s me ‘on me’ b. arnon ni on.1p us ‘on us’ Prepositional agreement with Object in Scottish Gaelic (ID275) (Byrne 2002, 85) (12) Cha robh fios agam air sin neg be.pst knowledge at.1s on that ‘I didn’t know that’ (‘There wasn’t knowledge at me about that’)

5.4.4 Definiteness The feature Definiteness includes a distinct number of occurring variants of definiteness marking. Definiteness is highly variating in Europe, Caucasus, and Asia, down to the level of individual languages (Bauer 2007), which we aim at targeting in our coding. We distinguish whether definiteness is marked on the adjective in the noun phrase (ADJ-DEF), whether there is a special word class of definite articles (DEF-ART, if definiteness is obligatory on the first element of the NP (DEF-FIRST), if definiteness is obligatory on the last element of the NP (DEF-LAST), and whether there is a suffix for definiteness (see table 18, examples 13–18). Definiteness marking falls out in 13 state combinations (table 19, appendix 2c) in the data. Definite article and suffix for definiteness on the noun in Swedish (ID270, 271) (13) det stor-a hus-et def large-def house-def ‘the large house’

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Tab. 18: Variants of the feature Definiteness marking, with reference to examples and ID (appendix 2a). VARIANT

QUESTIONNAIRE (y/n = 1/0)

EXAMPLE

ID

ADJ-DEF

Is there a suffix for definiteness on the adjective? This includes cases when the adjective has a different form in definite and indefinite NPs.

15, 13

271

DEF-ART

Is there a special word class of definite articles which occur in NPs without adjectives?

16, 15

269

DEF-FIRST

Is the definiteness marking obligatory on the first element of the NP?

18a–c

273

DEF-LAST

Is the definiteness marking obligatory on the last element of the NP?

17a–b

272

N-DEF

Is there a suffix for definiteness on the noun?

13

270

Tab. 19: State combinations for the feature Nominal morphology: Definiteness marking (for a complete list of the underlying order of variants and the combinations of 1/0, see appendix 2b). Number

Explanation

 1  2  3  4  5  6  7  8  9 10 11 12 13

No definiteness marking Definiteness on the first element of NP and definite article Definiteness marking on the adjective and on the noun Definiteness marking on the last element of the NP and on the noun Definiteness marking on the adjective and definite article Definite article and definiteness on the noun Definiteness on the noun Definiteness on the first element of the NP and definiteness on the noun Definiteness on the adjective Definite article Definiteness on the last element of the NP Definiteness on the last member of the NP, on the adjective, and on the noun Definiteness on the first member of the NP

Bound definite article in Swedish (ID270) (14) hus-et house-def ‘the house’ Bound definiteness marking on the adjective in German (ID269, 271) (15) das gross-e Haus def large-def house ‘the large house’ Non-bound definite article in German (ID269) (16) das Haus def house ‘the house’ Definiteness on the last member of the Noun Phrase in Basque (ID272) (Hualde and Ortiz de Urbina 2003, 119) (17) a. gizon-a man-def ‘the man’

5.4 Nominal morphology

b. gizon handi-a man big-def ‘the big man’ Definiteness on the 1st element of the Noun Phrase in Bulgarian (Halpern 1992:339) (ID273) (18) a. kniga-ta book-def ‘the book’ b. xubava-ta kniga nice-def book ‘the nice book’ c. moja-ta xubava kniga my-def nice book ‘my nice book’

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Map 11a: Definiteness marking.

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Map 11b: Definiteness marking.

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Map 11c: Definiteness marking.

5.5 Verbal morphology 5.5.1 Agreement in person, number and gender Under verbal morphology we target at first agreement patterns, i.e., inflectional morphology of verbs with respect to their syntactic environment (Bickel and Nichols 2007, 169–171). We use the same principle as with alignment, which means that we define a basic matrix, which we match against core constituents in various tenses. The matrix defined (cf. Baerman and Brown 2013) includes Full agreement, i.e., agreement with all persons and numbers, as found in, e.g., Tocharian (example 20), Gender agreement, aiming at agreement with respect to gender, as found in, e.g., Pashto (example 19) (Brugman and David 2014, chapter 8), and No agreement, as in, e.g., Swedish (example 20) (Holmes and Hinchliffe 2003, 214 ff.). These agreement types are tested against the core constituents S/A, O, and the case of the recipient or extended core (DAT), as in e.g., Basque (example 21). As with alignment, we check agreement patterns against present progressive and past tense, yielding six different agreement features (see table 20) plus allocutive agreement, which we have added for the inclusion of Basque (example 22a–b). Gender agreement in Pashto, Waziri dialect (Brugman and David 2014, 193) (19) 1 2 3 Present 3 Past

Masc. Fem. Masc. Fem.

Sg. -ǝm(a) -e -i, -o

Pl. -i -ǝy, -oy

-Ø, -ǝ, -ay -(ǝl)a

-ǝ(l) -(ǝl)e

This coding captures the typological variation in syncretism between full and no agreement. For the features Full agreement / No agreement, 1/0 implies that a language has agreement in all persons/numbers, 0/1 implies no agreement, whereas 0/0 includes a number of various types of

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Tab. 20: Features, occurring variants (V), attested state combinations of 1 and 0 (C), and explanation, for the grid Verbal morphology. GRID

FEATURE

V

C

EXPLANATION

Verbal morphology

Simple past, A

3

6

Verbal agreement, in simple past, in relation to A

Simple past, O

3

5

Verbal agreement, in simple past, in relation to O

Simple past, DAT

3

4

Verbal agreement, in simple past, in relation to DAT

Present progressive, A

3

5

Verbal agreement, in present progressive, in relation to A

Present progressive, O

3

4

Verbal agreement, in present progressive, in relation to O

Present progressive, DAT

3

3

Verbal agreement, in present progressive, in relation to DAT

Allocutive agreement

1

2

Occurence of allocutive agreement

Tab. 21: Variants of the feature Verbal morphology: Present progressive, A (see table 20). VARIANT

QUESTIONNAIRE (y/n = 1/0)

PROG:A-AGR-FULL

In present progressive: does the verb crossreference the agent in all persons/numbers?

PROG:A-Gender-AGR

In present progressive, does the verb agree in gender with the subject of a transitive verb?

PROG:NO-A-AGR

In present progressive: does the verb not crossreference the agent on the verb at all (e.g., Swedish)

syncretism in number/person (examples 11). The variant 1/1 is impossible (i.e., a language cannot have both no and full agreement). For this domain, the database has several shortcomings. For ancient Indo-European languages with full A-agreement in both present progressive and past tense, such as Tocharian, Greek, or Latin, the coding is representative for these categories. However, these languages, like several modern languages, e.g., of the Indo-Aryan or Slavic branches, have complex verbal systems for marking tense, aspect, and modality, with varying degrees of leveling in number and person endings, which the data set does not reflect. Much of the system complexity of ancient Indo-European languages is lost in several branches of the modern languages (Clackson 2007, 114 ff.), a transformation over time which is not reflected in the data in its current shape. Samples of full (a), syncretic (b) and no (c) Present progressive A-agreement, in Tocharian A (a), Gothic (b) and Swedish (c) (Krause and Thomas 1960, 262) (Bammesberger 1986, 34) (20)

a.

Sg.

Pl.

1 2 3 1 2 3

Tocharian A pälk- ‘shine’ pälkäm pälkät pälkäṣ pälkmäs pälkäc pälkiñc

b.

Gothic bindan ‘bind’ binda bindis bindiþ bindam bindiþ bindand

c.

Swedish sitta ‘sit’ sitter sitter sitter sitter sitter sitter

5.5 Verbal morphology

Indirect object agreement in Basque (ID291) (Hualde and Ortiz de Urbina 2003, 224) (21) eman d-i-zu-gu give 3sg.abs-aux-2sg.dat-1pl.erg ‘we have given it to you’ Allocutive agreement in Basque (ID294) (Hualde and Ortiz de Urbina 2003, 243) (22) a. Jon etorri d-u-k Jon come 3sg.abs-aux-2sg.m.alloc ‘Jon has come’ (familiar, male addressee) b. Jon etorri d-u-n Jon come 3sg.abs-aux.2sg.f.alloc ‘Jon has come.’ (familiar, female addressee)

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Map 12a: Agreement with respect to Agent (A) in Present Progressive.

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Map 12b: Agreement with respect to Agent (A) in Present Progressive.

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Map 12c: Agreement with respect to Agent (A) in Present Progressive.

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Map 13a: Agreement with respect to Agent in Simple Past.

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Map 13b: Agreement with respect to Agent in Simple Past.

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5.5.2 Tense By Tense we aim at capturing the typological profile of tense marking in languages, with a focus on the tenses present and future. Tense includes two features, Future and Continuous present (table 22). The typological profile of the Past is not included here; however, typological properties of tha Past are part of the Alignment as well as the Verbal morphology grids. The feature Continuous present targets the typology of marking of present progressive, with the variants Present (synthetic present, e.g., German die Sonne scheint, English the sun shines, ID300) and Progressive present (present formed by a present participle and a finite auxiliary verb, e.g., English the sun is shining, ID301, example 27). The feature has four state combinations (table 23). The feature Future targets the typological profile of the tense category future in languages (table 24). The data gives the state combinations future by auxiliary (as in English I will), future

Tab. 22: Features, occurring variants (V), attested state combinations of 1 and 0 (C), and explanation, for the grid Tense. GRID

FEATURE

V

C

EXPLANATION

Tense

Future Continuous present

5 2

16  4

Morphological typology, future Morphological typology, present progressive

Tab. 23: State combinations for the feature Continuous present (for a complete list of the underlying order of variants and the combinations of 1/0, see appendix 2b). Nr.

Explanation

1 2 3 4

Synthetic present progressive Auxiliary + participle present progressive Synthetic and auxiliary + participle present progressive Neither synthetic nor auxiliary + participle present progressive

Map 13c: Agreement with respect to Agent in Simple Past.

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Tab. 24: Variants of the feature Future, with example and ID (appendix 2a). VARIANT

QUESTIONNAIRE (y/n = 1/0)

ID

FUT.AUX

Is there a future formed by an auxiliary? (E.g., English I will)

295

FUT.Participle

Is there a future formed by a participle? (E.g., Armenian, Basque)

297

FUT.Particle

Is there a future formed by a particle preceding a finite verb? (E.g., Albanian)

298

FUT.Synth

Is there a synthetic future? (E.g., French, Spanish)

299

PERF.FUT

Is there a future formed by using the perfective aspect? (E.g., Russian, Georgian)

296

Tab. 25: State combinations for the feature Future, maps 14a–c (for a complete list of the underlying order of variants and the combinations of 1/0, see appendix 2b). Nr.

Explanation

 1  2  3  4  5  6  7  8  9 10 11 12 13 14 15 16

Future by auxiliary and by participle Future by auxiliary and synthetic future Future by auxiliary Synthetic future Future by particle No future Future by auxiliary and by particle Future by participle Future by participle and synthetic future Future by participle, synthetic future, and future by perfect Future by auxiliary, by particle, and synthetic future Future by auxiliary and by perfective Future by perfective Future by auxiliary, by participle, and synthetic future Future by particle and synthetic future Future by participle, by particle, synthetic future, and by perfective

by participle (examples 24, 25), future by a synthetic form, as in Spanish (example 26). Future by perfective aspect is found in e.g., Georgian (Kartvelian), which marks perfective aspect by using verbal prefixes, so-called preverbs; preverbs added to a verb in the present tense form the future perfective (example 23a–b) (Aronson 1989, 42). In total, the feature Future comes out as 16 state combinations (see table 25). Future by aspect in Georgian (ID296) (Revaz Tchantouria p.c.) (23) a. mxat’var-i xat’av-s surat-s artist paint-3sg.prs picture-dat ‘The artist paints a picture’ b. mxat’var-i da-xat’av-s surat-s artist prv-paint-3sg picture-dat ‘The artist will paint a picture’ Future by participle in Basque (ID297) (Hualde and Ortiz de Urbina 2003, 250) (24) ekarriko d-u bring-fut 3sg.abs-aux.prs.3sg.erg ‘He’ll bring it’

5.5 Verbal morphology

Future by participle and finite verb in Romanian (ID298) (Mišeska Tomić 2006) (25) a. o să dorm will comp sleep.1sg ‘I will sleep’ b. o să dormim will comp sleep.1pl ‘We will sleep’ c. o să dormiţi will comp sleep.2pl ‘You (pl.) will sleep’ Spanish synthetic future (ID299) (Bradley and Mackenzie 2004, 122) (26) hablaré speak.fut.1sg ‘I will speak’ Present progressive in Gaelic (ID301) (Byrne 2002, 99) (27) Tha mi a’ dol a-mach is 1sg prog go out ‘I am going out’

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Map 14a: Future tense marking.

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Map 14b: Future tense marking.

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5.6 Word order Word order (also: constituent order, order of meaningful elements) plays an important role in typological research (Greenberg 1966, Comrie 1989, Nichols 1992). The role of pragmatics, topicalization, information structure, and recursion, or the definition of boundaries between “free” and “fixed” word order are important aspects of word order typology. Word order encompasses 12 chapters of WALS (Dryer and Haspelmath 2013), and occupies a central role in, e.g., the EUROTYP project (Siewierska 1998). For this domain, there is a rich background literature as concerns contemporary languages. Word order is also important in evolutionary studies of language change, searching for deep-family correlations or lineage-specific trends in grammatical evolution (Levinson et al. 2011). In our coding, we aim at defining the default and dominant word order for a specific feature. We divide features by a relatively high level of granularity, according to clause structure, phrase structure, or the grammatical form of the predicate (see below and table 30). However, first we have to define what we imply by default and dominant (see 5.1.1). By default we imply the order used under normal spoken circumstances, e.g., excluding changes caused by topicalization, metrics in poetry, etc. By dominant we imply the order that has a statistical higher frequency, either in corpora (see further below), or in absolute numbers of forms in the grammar, e.g., for adpositions. We distinguish dominant by 70/30, meaning that 80/20 is coded as dominant (coding 1/0), whereas 60/40 (or 50/50, 40/60) is coded as poly-morphic behavior (coding 1/1). We compile data from ancient languages, which is particularly tricky when it comes to word order. There is also a rich literature in word order variation and change from a diachronic perspective (Schmidt 1982, Bauer 2000, Lühr 2015, Hirt 1937). Well-documented ancient languages, such as Vedic, Classical Latin, and Greek, for which tagged corpora are available, are well provided with literature on aspects of word order (Matic 2003, Zimmer 1976, Danckaert 2015). In these languages, basic word order is often described as “free” or varying in important aspects, such as OV/VO. Factors such as topicalization, formulaic language, style, and metrics play an important role in explaining the variety. In our data, key questions for coding are: – How do we identify a default word order? – How do we deal with a continuous change? – When do we code polymorphic behavior?

Map 14c: Future tense marking.

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Tab. 26: Change in percentages of OV vs. VO in classical Latin. Simplification after (Danckaert 2015). Author

Period

% OV

% VO

Plautus Terentius Cicero Caesar Pompei inscriptions Terentianus Vetus Vulgata

225–190 BCE 166–160 BCE Ca. 60 BCE Ca. 50 BCE Ca. 75 ACE Ca. 120 ACE Ca. 350 ACE Ca. 390–405 ACE

62 67 67 82 64 28 10 65

38 33 33 18 35 72 90 35

Tab. 27: Selected Word order coding for Latin and Old French (see also table 31). Feature

Coding for Latin

Coding for Old French

Adpositions Noun-adjective Noun-relative clause Noun-possessor WH-element Main clause Subordinate clause

Prep NA NRel N-Poss WH-initial SOV SOV

Prep NA NRel N-Poss WH-initial V2 SOV

As a key principle, we try to rely on corpus-based studies in deciding upon coding. In the case of a change, we use the archaic, more ‘classical’ variant as the selected preference. However, this is not always an easy decision to make, and, by necessity, the coding set-up of a language represents a simplification of a variation of a literary language. Looking at word order variation and change in Classical Latin (Danckaert 2015), we know that, like in most other ancient languages, both SVO, SOV, and OSV occur in the literature (example 28a–c). Looking at the statistics of change over time (table 26), we may identify a change in favor of VO in later literature over OV in classical literature, which becomes standard in Late Latin. This is not reflected in our selected coding for Latin (table 27). Instead, our coding reflects a static Classical Latin scenario. Word orders in Classical Latin (Danckaert 2015) (28) a. nec Hannibal detractuit certamen SVO and.not Hannibal.nom evade.pf.3sg battle.acc ‘and Hannibal did not avoid battle’ (Liv.aUc27.12.11) b. ibi Hannibal castra habebat SOV there Hannibal.nom camp.acc have.impf.3sg ‘there Hannibal held his army’ (Liv.aUc 21.45.4) c. ceteros Hannibal … in castra recepit OSV other.acc.m.pl Hannibal.nom in camp.acc receive.pf.3sg ‘the others Hannibal received in his camp’ (Liv. aUc 29.7.9) In Ancient Greek, we have a similar situation (Celano 2013, Dik 1995, Matic 2003, Lühr 2015). Texts, from Homeric to Classical and New Testament Greek, allow for great variation (see example 29a–b and table 28, 29), which might have a number of causes, of which pragmatics and topicalization seem to be the most prominent. Some scholars (Matic 2003, Haug 2009) propose

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Tab. 28: Word order distributions in Classical and NT Greek (Haug 2009, Ebeling 1903). Word order

Classical Attic (5–4 ct BCE)

NT main clauses (1st ct ACE)

SOV SVO OSV VOS VSO OVS OV VO

44,5 20,8 15,0  7,1  6,7  5,8 65 25

20,2 52,9  4,5  9,3  8,5  4,6 29 71

Tab. 29: Verbal positions in Classical Greek (Lühr 2015). Author:

Homer

Thycidides

Isocrates

Plutarch

Longus

Total

Verbs total V1 V2 Vend V middle

196  22  30  41 (21 %) 103 (53 %)

163  18  13  59 (36 %)  73 (45 %)

87  9  2 32 44

110  13  12  19  66 (60 %)

22  5  7  5  5

587  67  64 156 (27 %) 291 (50 %)

that a classification of Topic – Focus order would be more suitable for languages such as Ancient Greek. Example 29a–b. Word order in Classical Greek: SOV (a) and OSV (b) (29) a. Histiaîe basileùs Dareîos táde légei SOV Histiaeus king.nom.sg. Darius.nom this.acc say.prs.3sg ‘Histiaeus, Darius the king says the following’ (Hdt. 5.24.1) b. strouthò-n dè oudeìs élaben OSV ostrich-acc.sg. ptcp nobody.nom.sg. catch.aor.sg. ‘An ostrich, nobody caught.’ (Xen. An. 1.5.3) A great variety in word orders is also present in, e.g., Tocharian, both in A and B (examples 30, 31a–b). OV order occurs, both in metric and non-metric texts (examples 31a–b), even though it seems to be more prominent in metric texts (Carling 2017b, Zimmer 1976). Even so, a default word order can be identified with relative certainty (Carling 2017b, Schmidt 1982). Tocharian A order AN, SOV, and POSS-N (A1 a1) (30) kāsu ñom-klyu tsraṣi-śśi śäk kälyme-ntw-aṃ good.nom.sg. name-reputation.nom.sg. energetic-gen.pl. ten direction-obl.pl-loc sätk-atär spread-prs.3sg ‘the good name and reputation of the energetic ones is spreading in ten directions’ (A1 a1) Tocharian A subordinate clause with O-S-Subj.-V (A 73 b4, metrical) (31) a. puk wramn-aṃ käpñune säm kuprene ṣyak krop-i-tär all thing-loc love he.nom.sg.m if together collect-opt-3sg.mpass ‘if he compiled together all his love to all things’ (A 73 b4, metrical)

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Tab. 30: Word order: features, occurring variants (V), attested combinations of 1 and 0 (C), and explanation. GRID

FEATURE

V

C

EXPLANATION

Word Order

Adpositions Noun-adjective Noun-relative clause Noun-Possessor WH-element Main clause Subordinate clause Infinitive Participle Clitic pronouns finite verb Clitic pronouns infinitive Clitic pronouns participle

2 2 2 2 2 4 4 2 2 3 3 3

4 3 4 3 4 5 5 4 4 5 5 5

Noun / adposition word order Noun / adjective word order Noun / relative clause word order Noun / possessor word order Position of WH-element Main clause word order Subordinate clause word order Infinitive word order Participle word order Clitic pronoun finite verb word order Clitic pronoun infinitive word order Clitic pronoun participle word order

Tocharian A OSV word order (A 151 b4, non-metrical) (31) b. umparñ-aṃ wkäṃ ya-ṣ säm ñare-yntw-aṃ kuprene evil-obl.sg.m manner.obl.sg go-3sg.prs he.nom.sg. hell-obl.pl-loc if cma-tär be-born.sbjv-3sg.mpass ‘he [having] evil manner goes to hell, if reborn’ (A151 b4, not metrical) Compared to Latin and Greek, mentioned earlier in the text, Tocharian is different. Though being an entirely literary language, attested from a relatively long period (Tocharian A ca. 500– 1000 ADE, Tocharian B ca. 400–1100 ADE), there is no traceable ongoing typological change, e.g., in word order, from earlier to later texts. In sum, word order is a type of feature where we have a variation in a documented corpus of a language, for which our model forces a selection either of a preferred variant or polymorphic behavior, i.e., coding of both or all (cf. 5.1.3). One problem is how to deal with an attested change. In the current model, where there are defined languages, e.g., Latin, Classical Greek, Tocharian A or Tocharian B, there is no way to distinguish a changing from a static language. This might have a potential impact on computational models. E.g., Latin is coded as SOV, whereas the Old Romance languages are coded as SVO. A computational model unaware of the fact that the change SOV → SVO happened once in Latin, might interpret the change SOV → SVO as if it happened multiple times in parallel between Latin and Old Romance languages, which we know not to be the case. A possible way out is to add further language states, such as, ‘Late Latin’, ‘Koine Greek’, ‘NT Greek’. However, if we cut languages into smaller units (e.g., stages, dialects), we need to reconsider commensurability over the entire set. For this reason, we do not divide languages into smaller units, even though there is an ongoing change for an individual feature. Using a matrix of basic patterns, we divide word order into a number of features with reference to order of core constituents S/A, O, and V, head and modifier in NPs, relative markers, and clause structure. The targeted features are listed in table 30, together with number of occurring variants and attested state combinations of 1 and 0 in the data set. The full set of word orders is given in table 31.

Infinitive

Subordinate clause

Main clause

WH-element

Noun-possessor

Noun-relative clause

232

230

OV

What is the canonical (neutral) word order in a subordinate clause?

SOV

229

231

What is the canonical (neutral) word order in a subordinate clause?

VSO

228

227

226

225

224

223

222

221

220

219

218

217

216

215

214

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ID

VO

V2 implies that initial adverb triggers V-SUBJ word order (Swedish, German etc.).

What is the canonical (neutral) word order in a main clause?

SOV

V2

What is the canonical (neutral) word order in a main clause?

VSO

What is the canonical (neutral) word order in a subordinate clause? NB: V2 languages like Swe and Ger do NOT count as SVO even though SVO is most frequent.

V2 implies that initial adverb triggers V-SUBJ word order (Swedish, German etc.).

V2

SVO

What is the canonical (neutral) word order in a main clause? NB: V2 languages like Swe and Ger do NOT count as SVO even though SVO is most frequent.

Does the WH-question word always immediately precede the verb (i.e., stand directly before the verb)?

WH-V

SVO

Is the WH-question word always obligatorily the first element in a question?

Do most possessors occur before the noun they possess? The possessor should be an animate noun, and neither a proper name nor a pronoun!

Poss-N

WH-initial

Do most possessors occur after the noun they possess? The possessor should be an animate noun, and neither a proper name nor a pronoun!

Do most relative clauses occur before the noun?

RelN

N-Poss

Do most relative clauses occur after the noun?

Do most adjectives occur before the noun?

AN

NRel

Do most adjectives occur after the noun?

NA

Does the language have a substantial set of postpositions?

Post

Noun-adjective

Does the language have a substantial set of prepositions? E.g. English in the house

Prep

Adpositions

Explanation

Variant

Feature

Tab. 31: Features and variants of Word order in the corpus.

50

49

48

47

46a–b

45

44

43

42

41

40

38–39

37, 39

36

35

33, 34

32

Example

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Clitic pronouns participle

Clitic pronouns infinitive

243

nd

Does the clitic pronoun always occur in 2nd position, not specifically before or after the verb?

242

OV

2

241

VO

position

240

nd

Does the clitic pronoun always occur in 2nd position, not specifically before or after the verb?

239

OV

2

238

VO

position

237

nd

Does the clitic pronoun always occur in 2nd position, not specifically before or after the verb? (Wackernagel position)

236

OV

2

235

VO

position

234

OV

Clitic pronouns finite verb

233

VO

ID

Participle

Explanation

Variant

Feature

Tab. 31 (continued)

61

60

59

57,58

56a–b

55

53, 54

52

51

Example

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Noun-Adposition Word order in Finnish (ID214) (p.c. Sandra Cronhamn) (32) Koira on sängy-n alla. dog is bed-gen under ‘The dog is under the bed’ Noun-Adjective Word order in Basque (ID215) (Hualde and Ortiz de Urbina 2003, 119) (33) gizon handi-a man big-def ‘The big man’ Noun-Adjective Word order in Scottish Gaelic (ID215) (Byrne 2002, 47) (34) Fhuair sinn cat dubh got 1pl cat black ‘We got a black cat’ Adjective-Noun Word order in Finnish (ID216) (p.c. Sandra Cronhamn) (35) Anna-lla on sininen pusero Anna-ad cop blue shirt ‘Anna has a blue shirt’ Noun-Relative clause Word order in Swedish (ID217) (p.c. Arthur Holmer) (36) Jag förlora-de peng-ar-na [som Pelle gav mig] I lose-prt money-pl-def rel Pelle give.prt me ‘I lost the money that Pelle gave me’ Relative clause-Noun Word order in Basque (ID218) (Hualde and Ortiz de Urbina 2003, 764) (37) [Pellok ekarri du-en] diru-a galdu d-u-t Peter.erg bring 3sg.abs-aux.3sg.erg.comp money-def lose 3sg.abs-aux-1sg.erg ‘I lost the money Peter brought’ Noun-Possessor Word Order in Scottish Gaelic (ID219) (Byrne 2002, 21, 34) (38) Pàrlamaid na h-Alba Parliament def Scotland ‘the Scottish Parliament (the Parliament of Scotland)’ (39) Sin càr mo sheanmhar that car 1sg.poss grandmother.gen ‘That is my grandmother’s car’ WH-first Word order in Finnish (ID221) (Karlsson 1999, 74) (40) Missä Auli on? where Auli be.3sg ‘Where is Auli?’

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WH-V Word order in Basque (ID222) (Hualde and Ortiz de Urbina 2003, 521) (41) Horrelakoak nork egin ez ditu (ba)? such.things who.erg do not aux so ‘Who didn’t (ever) do such a thing? V2 order in Main clause in Kashmiri (ID224) (Wali and Koul 1997, 45) (42) a. səli:m gav ra:th ra:jas sɨ:t’ ba:gas manz Salim.abs went yesterday Raj with garden in ‘Salim went in the garden with Raj yesterday’ b. ba:gas manz gav səli:m ra:th ra:jas sɨ:t' garden in went Salim.abs yesterday Raj with ‘Salim went in the garden with Raj yesterday’ Main clause VSO Word order in Welsh (ID225) (Borsley, Tellerman, and Willis 2007, 33) (43) Gwelodd Rhiannon ddraig see.pst.3s Rhiannon dragon ‘Rhiannon saw a dragon’ Main clause SOV Word order in Basque (ID226) (Hualde and Ortiz de Urbina 2003, 450) (44) Jon Mikel ari da ikusten Jon Mikel prog aux see.impf ‘Jon is seeing Mikel’ Subordinate clause SVO Word order in Swedish (ID227) (Arthur Holmer p.c.) (45) Pelle är glad [eftersom Lisa har köp-t bok-en] Peter is happy since Lisa have.prs buy-sup book-def ‘Peter is happy since Lisa has bought the book’ V2 Subordinate clause Word order in Icelandic (Holmberg and Platzack 1995, 79) (ID228) (46) a. Jón sagði að þessa bók hef-ði ég átt að lesa Jon said comp this book have-pst I ought to read ‘Jon said that I should have read this book’ b. Jón harma-r að þessa bók hefði ég átt að lesa Jon regret-prs comp this book have-prt I ought to read ‘Jon regrets that I should have read this book’ Subordinate clause VSO in Welsh (ID229) (Borsley, Tellerman, and Willis 2007, 33) (47) Dw i ’n credu [(yr) hoffai Gwyn fynd adre.] be.prs 1sg prog believe prt like.cond.3sg Gwyn go.inf home ‘I believe that Gwyn would like to go home’

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Subordinate clause SOV in Kashmiri (ID230) (Wali and Koul 1997, 67) (48) [yeli bɨ sɔmmarg chus gatsh-a:n] teli chu su ti gatsh-a:n when 1sg Sonmarg-to am gone then is he too goes ‘When I go to Sonmarg, (then) he goes too’ VO with INF in Swedish (ID231) (p.c. Arthur Holmer) (49) Jag lycka-de-s sälja min båt 1 succeed-pst-pass sell.inf my boat ‘I succeeded in selling my boat’ OV Word order with Infinitive in Modern Irish (ID232) (Brothers 1980, 128) (50) Theip orm an bád a dhíol failed on.me def boat inf sell ‘I failed to sell the boat’ VO Word order with Participle in Modern Irish (ID233) (Brothers 1980, 129) (51) Tá sí ag crú na mbó is she prog milk def cow.pl.gen ‘She is milking the cows’ OV Word order with Participle in Dutch (ID234) (Shetter and Ham 2007, 137) (52) Hij heft het geld aangenomen he aux.3sg def money accept.pst.prt ‘He accepted the money’ Clitic pronoun Finite verb VO Word order in Old Spanish (ID235) (Rivero 1986, 778) (53) El rrey recibio-lo muy bien def king received-him very well ‘The king received him very well’ Clitic pronoun Finite verb VO Word order in Portuguese (ID235) (Hutchinson and Lloyd 1996, 45) (54) Eu levo-te à estação I take.1sg-2sg to.def station ‘I’ll take you to the station’ Clitic pronoun Finite verb OV Word order in Spanish (ID236) (Uriagereka 1995, 92) (55) Lo oimos it heard.1pl ‘We heard it’

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Clitic pronoun Finite verb 2nd position Word order in Croatian (Serbo-Croatian in source) (ID237) (Anderson 1993, 73) (56) a. Taj mi je pesnik napisao knjigu. that 1sg.dat pst poet wrote book ‘That poet wrote me a book’ b. Taj pesnik mi je napisao knjigu ‘that poet 1sg.dat pst wrote book ‘That poet wrote me a book’ Clitic pronoun Infinitive VO Word order in Spanish (ID238) (Uriagereka 1995, 92) (57) Para oir-lo to hear-it ‘To hear it’ Clitic pronoun Infinitive VO Word order in Italian (ID238) (Kayne 1991, 648) (58) Parlargli sarebbe un errore speak.inf.him.dat would-be an error ‘It would be a mistake to speak to him’ Clitic pronoun Infinitive OV Word order in French (ID239) (Kayne 1991, 648) (59) Lui parler serait une erreur 3sg.m.dat speak.inf would-be an error ‘It would be a mistake to speak to him’ Clitic pronoun Participle VO Word order in Spanish (ID241) (Butt and Benjamin 1994, 139) (60) Estoy contá-ndo-te-lo be.1sg tell-prs.prt-2sg-3sg ‘I am telling it to you’ Clitic pronoun Participle VO Word order in French (ID242) (Batchelor and Chebli-Saadi 2011, 275) (61) Elle a été surprise en me voyant. she aux been surprised.fem at 1sg see-prs.prt ‘She was surprised on seeing me’

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Map 15a: Word order Adposition − Noun.

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Map 15b: Word order Adposition − Noun.

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Map 15c: Word order Adposition − Noun.

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Map 16a: Word order Noun − Adjective.

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Map 16b: Word order Noun − Adjective.

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Map 16c: Word order Noun − Adjective.

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Map 17a: Word order Noun – Relative clause.

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Map 17b: Word order Noun – Relative clause.

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Map 17c: Word order Noun – Relative clause.

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Map 18a: Word order Noun – Possessor (Genitive).

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Map 18b: Word order Noun – Possessor (Genitive).

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Map 18c: Word order Noun – Possessor (Genitive).

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Map 19a: Position of Question word.

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Map 19b: Position of Question word.

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Map 19c: Position of Question word.

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Map 20a: Word order in Main Clauses.

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Map 20b: Word order in Main Clauses.

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Map 20c: Word order in Main Clauses.

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Map 21a: Word order Subordinate Clause.

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Map 21b: Word order Subordinate Clause.

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Map 21c: Word order Subordinate Clause.

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Map 22a: Word order Object – Infinitive.

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Map 22b: Word order Object – Infinitive.

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Map 22c: Word order Object – Infinitive.

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Map 23a: Word order Object − Participle.

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Map 23b: Word order Object − Participle.

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Map 23c: Word order Object − Participle.

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Map 24a: Word order Clitic Pronoun – Finite Verb (Predicate).

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Map 24b: Word order Clitic Pronoun – Finite Verb (Predicate).

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Map 24c: Word order Clitic Pronoun – Finite Verb (Predicate).

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Map 25a: Word order Clitic Pronoun – Infinitive Verb.

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Map 25b: Word order Clitic Pronoun – Infinitive Verb.

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Map 25c: Word order Clitic Pronoun – Infinitive Verb.

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Map 26a: Word order Clitic Pronoun – Participle Verb.

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Map 26b: Word order Clitic Pronoun – Participle Verb.

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5.7 Analyzing the data: synchronic and diachronic models 5.7.1 Cluster analysis and geographic distribution of groups To conclude our section on grammar data and before evaluating and discussing our results, we want to perform an analysis based on all the grammar data, not just the features selected for the map visualizations of previous chapter. Our first model of analysis is synchronic. This means that we analyse our complete set of data in all of our languages independent of their internal phylogenetic relations or their temporal distribution. In this, we also look aside from internal dependencies between grids, features, and variants: the data set is seen as a string of binary values in languages where all values are equally independent. There are several methods for clustering data for a purpose such as this. One method, which we have tested in a previous publication (Carling, Larsson, et al. 2018), is to calculate pairwise linguistic distance between languages in our data, based on our current feature set. The result is relatively noisy-looking, but has large similarities with the model we test for the current atlas, where our main aim is to find a model that gives a meaningful spatial correlation. Maps 27a–c visualize the grammar data by apportioning the 148 languages with grammar data in DiACL into just 10 similarity-based groups, or clusters. In this instance, the clustering method used is so-called soft clustering, which permits each language to belong in various proportions to more than one cluster. This has the benefit of revealing the multiple resemblances that any one language may have to others. The clustering algorithm used here is Structure (Pritchard, Stephens, and Donnelly 2000). Structure does not reconstruct the evolutionary paths of change. The similarities visualised in maps 27a–c, even though they reflect a historical development, are synchronic. Structure is widely used in population biology, and consequently many descriptions of it in the literature focus on the specifically biological interpretations of its underlying mathematics. The underlying math though is not specifically biological, rather it is an elegant application of Bayesian statistics to the question: if we assume K clusters (here, K = 10) then what is the most likely apportionment of (a) features to clusters, and (b) languages to clusters, so that features and languages are linked to one another, mediated by the K clusters, where “linked to” is interpreted via a simple probabilistic equation. The Structure algorithm finds an-

Map 26c: Word order Clitic Pronoun – Participle Verb.

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swers to both (a) and (b). Our maps show the answer to (b): the various, fractional apportionment of languages to clusters, shown as pie charts, colour-coded by cluster. The same information is presented in fig. 6, where each slender horizontal slice represents one language, and the colours are its fractional apportionment to various clusters. Information on the answer to (a) is presented compactly in the tree-like diagram in fig. 6. Again, this is not a historical tree but indicates the pairwise mutual similarities of the ten clusters defined in terms of their features: if you traverse the tree from one cluster to another, then the shorter the route, the more similar are the features of those two clusters. We experimented on setting K to various different numbers, but it turned out that 10 was the number that gave the most appropriate result, with little admixture and confusion between groups. In maps 27a–c, the soft clusters are capable of reflecting synchronic affiliations that have arisen via multiple historical processes, including conserved similarity due to shared inheritance, parallel development due to drift, divergence owing to accumulated independent changes, and convergence due to language contact. To make our maps more intuitive to read, we have given the ten clusters impressionistic labels (which are to be understood as geographical labels rather than phylogenetic subgroupings). The labels are not part of the analysis; they are an aid to finding one’s way around the maps. When we instruct Structure to reduce 148 languages down to just 10 clusters, we are demanding that a large amount of information be summarised into just 10 categories. Of necessity, much detail is lost. Like any other summarising tool, the Structure-based visualisation here is useful to the extent that the summary reveals something of interest. We believe that Structure does this, moreover, it does so using a reproducible, automated technique that is not biased by our own preconceptions of what it “ought to” find. The results will be evaluated in 5.8.

5.7 Analyzing the data: synchronic and diachronic models

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n ami Albanian_Tosk an

3

Serbian Slovene Slavonic rman _German

German h German n

ish

elic on h h reek k k

ese Sicilian

al Tocharian_A

e erash ra

Assamese Sinhalese

on nian ian Gilaki ani

lkar

n Svan

Figure 6: Structure analysis on typological data (all features, all languages), dividing into 10 clusters, including a tree diagram of pairwise mutual similarities between clusters.

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Map 27a: Pie chart map showing distribution of clusters of fig. 6 (modern languages).

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Map 27b: Pie chart map showing distribution of clusters of fig. 6 (historical languages).

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Map 27c: Pie chart map showing distribution of clusters of fig. 6 (Romani).

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5.7.2 A diachronic model of evolutionary reconstruction Based on the grammar data, we also try out a diachronic model of evolutionary reconstruction. The main description of the procedure and results are found elsewhere (Carling and Cathcart Forthcoming). As described earlier in this volume (3.3), the model of morphosyntactic reconstruction introduced by the scholars of comparative Indo-European in the 19th ct. was mainly based on comparative reconstruction of grammar morphology, systematizing forms and meanings in a manner that complete paradigms, rules and meanings could be reconstructed to a proto-language. However, even though morphemes, just as lexemes, can be safely reconstructed by comparative method, there are problems of reconstructing the syntactic meanings, due to the lack of regularity, the lack of arbitrariness, and the absence of directionality of syntactic meaning (Barðdal 2014). A major obstacle to morphosyntactic reconstruction is the so-called “correspondence problem” (Roberts 2007, 363–367, Walkden 2013): we may reconstruct a pattern to an ancestral state of several daughter languages carrying the same pattern, but in the case of disagreement, we do not know enough about the directionality of morphosyntactic change to reconstruct one variant over another. Nevertheless, the morphosyntactic reconstruction model is applied by a number of scholars; even though there is agreement that the method should not be applied to all properties, in particular properties that are not constrained by morphology, e.g., word order (Harris and Campbell 1995, Harris 2008). Proponents of syntactic reconstruction argue that if a specific pattern, aided by morphosyntactic reconstruction, has survived in a majority of languages, then there is reason to reconstruct it to the proto-language (Campbell and Harris 2002, 615). The model of morphosyntactic reconstruction used by the typologists from the 1960s and on is based upon another principle, namely implicational dependencies and order of meaningful elements in language (Greenberg 1966, Nichols 1992, Enfield 2017). If language-internal implicational dependencies between features (“universal” patterns) can be identified, based on an observation of patterns in unrelated languages, then these observations can be used as an argument for reconstructing typological properties to a proto-language. A major problem to the adaptation of this model are the cases of language-internal conflicts between features with respect to assumed dependencies. A good example is the controversy on Indo-European word order (Lehmann 1974, Friedrich 1975). Evolutionary models of syntactic reconstruction rely basically on reconstructive rather than dependency models; here, the issue of reconstruction is addressed probabilistically using evolutionary methods. The probability of the presence of a morphosyntactic property (coded as a feature) at an ancestral proto-language is estimated on the basis of a tree topology, the distribution of the feature among the daughter languages, and an evolutionary model of change (Maurits and Griffiths 2014, Dunn et al. 2017, Cathcart et al. 2018). Basically, the model does not account for directionality of morphosyntactic change (e.g., grammaticalization) or implicational dependencies between features (“universals”). The model uses a reference tree topology, based on either comparative method (“hand-crafted”), or a tree sample from lexical data, typically basic vocabulary (fig. 3). Thereupon, evolutionary rates for a feature (multistate, individual) are estimated, under the assumption that the feature evolves according to a Continuous-time Markov process. For this type of model, a maximum likelihood estimate of the rates can be obtained; alternatively, we can sample from the posterior distributions of the rates via Markov chain Monte Carlo. Once evolutionary rates have been estimated, the probability of the presence of the feature in question can be estimated for internal nodes of the tree, including the root – the node ancestral to all of the attested languages in the sample (Felsenstein 2004, Yang 2014) (see fig. 7). Different from a synchronic clustering (5.7.1), an evolutionary reconstruction can be executed on language families only. We perform an evolutionary reconstruction on the Indo-European data of our corpus. To improve the results of the reconstructions, we recode features into multistate characters of higher granularity than the state combinations used in the geographic visualizations of the maps (5.3–5.6). Basically, we follow the feature groupings (corresponding to the

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?

?

a

b

b

Figure 7: Visualization of the process of computer-based ancestral state reconstruction of features, such as comparative concepts in grammar. The probability that a feature/variant is present at a given node is estimated, based on the evolutionary rates inferred for the feature/variant, as well as the probability that the feature/variant is present in descendant nodes.

state combinations of maps) for domains Alignment, Verbal morphology, and Word order. For Nominal morphology, we basically, with a couple of exceptions, treated the variants as separate units. An extract of the most important results are given in table 32. It is evident that the evolutionary reconstruction produces a result for Proto-Indo-European that is more in line with the canonical model of Indo-European syntax (nominative-accusative, highly synthetic) (Brugmann, Delbrück, and Delbrück 1900) than any other, alternative (isolating, ergative) model (Gamkrelidze and Ivanov 1984, Uhlenbeck 1901, Hirt 1934). To summarize the most important results of the reconstruction (Carling and Cathcart Forthcoming), we notice that the evolutionary reconstruction produces a high probability (0.63) for nominative-accusative marking in present progressive (table 32:1), and a medium-high probability (0.63) for nominativeaccusative marking also in the simple past (table 32:2). In contrast, the probability for no marking is low in present progressive (0.33) and in simple past (0.33), but the ergative appears at a low probability (0.12) also in the simple past (table 32:1–2). As for nominal morphology, we have a somewhat higher probability for case marking on the adjective in a Noun Phrase (0.55) than no case marking on the adjective (0.44) (table 32:3). We also have a high probability for case marking on the noun in a Noun Phrase (0.74). Further, the evolutionary reconstruction points the direction of a three-gender system of Proto-Indo-European, with a high probability of a masculine/feminine distinction (0.65), a very high probability of a neuter gender (0.86), and a high probability of gender marking on a predicative adjective (0.64) (table 32:5–7). This goes against the mainstream view of the Proto-Indo-European gender system, which reconstructs only two genders, a masculine (animate) and a neuter (inanimate) (Matasović 2004, Tichy 1993). As for the case system, we have a high probability (0.7) for a distinction between Agent and Object in nouns (table 32:8), which is even more pronounced in pronouns (0.93) (table 32:11). However, in nouns we have a lower probability for genitive and dative (0.41) as well as to have more than 7 cases (0.39) (table 32:9). Looking at verbal morphology, we have a higher probability for full Agent agreement (0.55) over syncretic Agent agreement (0.32) in present progressive (table 32:12), compared to the simple past, where we have a higher probability for syncretic Agent agreement (0.37) over full Agent agreement (0.26) (table 32:13). All these results, including the three-gender system, align with the morphosyntactic reconstruction found in the traditional reconstuction of the Neogrammarians in the 19th century (Brugmann, Delbrück, and Delbrück 1900, Meier-Brügger, Fritz, and Mayrhofer 2010). Moving over to word order, we notice some interesting tendencies in our results. Since Greenberg (Greenberg 1966, 1963), order of meaningful elements plays a central role in all typological research including computational models (Dunn et al. 2011, Croft et al. 2011, Baker 2011, Bickel 2011b, Cysouw 2011, Donohue 2011). (see 5.6), but in diachronic syntax, the reconstruction of word order remains a controversial issue. Greenberg’s observations of implicational relations of order of head and dependent (Lehmann 1973), were in the approach by Nichols defined as dependency types, which were regarded as stable both geographically as well as diachronically (though with regional skewing patterns) (Nichols 1992, 1995, 1998). In diachronic syntax, the reconstruction of word order cannot be immediately based on any morphosyntactically reconstructable language material (cf. Roberts 2007, 175–198). Therefore, re-

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construction of word order are based either on actual observation in attested languages or connections to other properties in language, which can be either reconstructable or not. Consistency and harmony, as well as stability in word order patterns, is central in the model of reconstruction, both by Lehmann and Nichols (Lehmann 1973, 1974, Nichols 1992), and this is also one of the major sources of criticism against word order reconstruction (Lightfoot 2002, Watkins 1976). It is evident that word order consistency is not entirely regular: a large percentage of languages show exceptions in consistency, indicating that consistency cannot be used as a sole argument for reconstruction (Campbell and Harris 2002, Harris and Campbell 1995). Hence, word order in Proto-Indo-European is an old controversy, beginning with Delbrück (Delbrück 2010, 38–111) and the study on the position of clitics by Wackernagel (Clackson 2007, 168, Wackernagel 1892). There are two competing positions on Proto-Indo-European word order, both of which require a consistency approach. Much of the critique of the word order reconstructions delves around problem of establishing a default order in ancient languages, which form the basis for a proto-language reconstruction (Winter 1984) (see 5.6). Other researchers highlight the general problems of word order reconstruction due to the inherent problem of reconstructing variation and change (Pires and Thomason 2008, Lightfoot 2002). The mainstream position, which ultimately goes back to Delbrück, assumes verb-finality (OV) and head-final order for noun phrases (Lehmann 1973, 1974, 1993, 2002, Hock 2013, Mallory and Adams 1997). The competing position, which bases its discussion on problems of Proto-Indo-European relative clauses, assumes VO order for Indo-European (Friedrich 1975). Considering the results of the evolutionary reconstruction (table 32), we notice a high probability of SOV in main clauses (0.81), as well as in subordinate clauses (0.80) for Proto-IndoEuropean (table 32:16, 21). Further, we have a high probability for Noun – Adposition (0.81) (table 32:14–15), Possessor – Noun (0.60) (table 32:17), and Adjective – Noun (0.80) (table 32:17). These results correlate with the mainstream view on Proto-Indo-European as a head-first language (Lehmann 1974). On the other hand, we have a high probability of Noun – Relative clause (0.65) over Relative clause – Noun (0.28). The position and construction type of the relative clause was a main source of conflict between Lehmann and Friedrich, and has been extensively discussed in Indo-European syntax (cf. Hock 2013, Watkins 1976). In accordance with the consistency theory by Greenberg (Greenberg 1963), continued by Lehmann (Lehmann 1973, 1974), an OV language naturally has Relative clause – Noun (cf. Harris and Campbell 1995, 363–367), which is also the case in several of the archaic languages, such as Sanskrit and Homeric Greek (Delbrück 2009, 295–345). However, Hittite (paralleled in, e.g., Latin) has the reverse order, Relative clause – Noun, which is inconsistent with OV (see Clackson 2007, 171–176 for an overview). Our result reconstruct an inconsistent pattern for Proto-Indo-European. Even though the result is only indicative, basically due to rough definition of relative clauses (NRel/RelN), which does not distinguish, e.g., correlative – relative clauses, type of clause relation (paratactic or hypotactic), or restrictive – non-restrictive relative clause, it is noteworthy considering its importance to the consistency model meantioned before. The current description of evolutionary reconstruction of grammar gives an insight in the advantages of an evolutionary model. A model or reconstruction such as this may be highly useful for other types of testings, such as areal pressure in grammar evolution (Cathcart et al. 2018), temporal stability, or tendency to drift (Round et al. Forthcoming). Ultimately, the causalities for large-scale convergence as well as tendency to diverge both hide within the grammar itself as well as in ist environment. By statistical and empirical tests, these causalities can be unveiled.

6

5

4

3

2

1

Variant

A=O? 0 0 1

A=O? 0 0 0 1

NEUTR 0 1

Nominal morphology|Gender / Noun class

M/F 0 1

Nominal morphology|Gender / Noun class

CASE-N 0 1

Nominal morphology|Case marking

CASE-ADJ 0 1

Nominal morphology|Case marking

O=So? 0 0 1 1

Alignment|Noun: Simple Past

O=So? 0 0 1

Alignment|Noun: Present Progressive

Variant

A=Sa? 0 1 0 1

A=Sa? 0 1 1

Variant

Sa=So? 1 1 1 1

Sa=So? 1 1 1

Variant

0.137275 0.862725

0.3409 0.6591

0.25135 0.74865

0.4483 0.5517

0.041225 0.526275 0.122925 0.309575

0.03415 0.631175 0.334675

Probability

No neuter gender Neuter gender

No masculine/feminine distinction Masculine/feminine distinction

No case on noun Case on noun

No case on adjective Case on adjective

Noun, Simple past: Tripartite Noun, Simple past: Nominative-accusative Noun, Simple past: Ergative Noun, Simple past: No marking

Noun, Present progressive: Tripartite Noun, Present progressive: Nominative-accusative Noun, Present progressive: No marking

Interpretation

Tab. 32: Samples of reconstruction of multistate characters of the grammar data set (Indo-European languages only). For each multistate character, the likelihood of a set of evolutionary transition rates between each pair of states under a tree topology and observed data are computed according to Felsenstein’s Pruning Algorithm, which is used to estimate the probability of a state at the root of the tree. We use RStan to infer the posterior probabilities of these rates, marginalizing over a sample of trees. Numbers of the first column are for reference and refer to features (appendix 2a), the following set of variants (appendix 2a) represent our defined multistate characters, the column Probability gives the state probability at the root of the tree, and the column Interpretation explains the multistate character as a linguistic property. Extracted from (Carling and Cathcart Forthcoming).

166 5 Atlas: Grammar

12

11

10

9

8

7

Variant

GEN 0 1 0 1

A-AGR-FULL 0 0 0 1 1

A-Gender-AGR 0 0 1 0 1

Verbal morphology|present progressive, A

A≠O 0 1

Nominal morphology|Pronominal Cases

DAT 0 0 1 1

Nominal morphology|Nominal cases

OBL-Cases 0 1

Nominal morphology|Nominal cases

O-case 0 1

Nominal morphology|Nominal cases

PRED-ADJ 0 1

Nominal morphology|Gender agreement

Variant

Tab. 32 (continued)

NO-A-AGR 0 1 0 0 0

GEN/DAT 0 0 0 1

Variant

Variant

0.32185 0.059775 0.040125 0.55075 0.0275

0.069525 0.930475

0.318175 0.106275 0.0599 0.411025

0.02195 0.97805

0.290025 0.709975

0.356075 0.643925

Probability

Present progressive: Syncretic A Agrement Present progressive: No A Agreement Present progressive: Gender A Agreement Present progressive: Full A Agreement Present progressive: Full and Gender A Agreement

No difference A and O (pronouns) Difference A and O (pronouns)

No genitive or dative Genitive but no dative Dative but no genitive Genitive and dative

No peripheral cases Peripheral cases

No case difference A and O Case difference A and O

No gender on predicative adjective Gender on predicative adjective

Interpretation

5.7 Analyzing the data: synchronic and diachronic models

167

18

17

16

15

14

13

Variant

SVO 0 0 1 0 1

A-Gender-AGR 0 0 1 0 1

Poss-N 1 0 1

AN 0 1 1

NA 1 0 1

Word order|Noun-adjective

N-Poss 0 1 1

Word order|Noun-Possessor

SOV 0 0 0 1 1

Word order|Main clauses

Prep 0 1

Word order|Adpositions

Post 0 1

Word order|Adpositions

A-AGR-FULL 0 0 0 1 1

Verbal morphology|simple PAST, A

Variant

Tab. 32 (continued)

V2 0 1 0 0 0

NO-A-AGR 0 1 0 0 0

Variant

VSO 1 0 0 0 0

Variant

0.143575 0.80045 0.055975

0.602725 0.337375 0.0599

0.0193 0.0603 0.08145 0.8292 0.00975

0.7149 0.2851

0.18925 0.81075

0.378725 0.192675 0.063375 0.264475 0.05805

Probability

Noun – Adjective Adjective − Noun Adjective – Noun and Noun – Adjective

Possessor − Noun Noun − Possessor Possessor – Noun and Noun – Possessor

Main clause: VSO Main clause: V2 Main clause: SVO Main clause: SOV Main clause: SOV/SVO

No Prepositions Prepositions

No Postpositions Postpositions

Simple past: Syncretic A Agreement Simple past: No A Agreement Simple past: Gender A Agreement Simple past: Full A Agreement Simple past: Full and Gender A Agreement

Interpretation

168 5 Atlas: Grammar

22

22

21

20

19

Variant

VO 1 0 1

RelN 0 1 0 1

WH-initial 0 1

Word order|WH-element

WH-V 0 1

Word order|WH-element

SOV 0 0 0 1 1

SVO 0 0 1 0 1

Word order|Subordinate clause

OV 0 1 1

Word order|Participle

NRel 0 0 1 1

Word order|Noun-relative clause

Variant

Tab. 32 (continued)

V2 0 1 0 0 0

Variant

VSO 1 0 0 0 0

Variant

0.233875 0.766125

0.73015 0.26985

0.03845 0.025075 0.12125 0.802725 0.0125

0.0656 0.885025 0.049375

0.0276 0.284575 0.65935 0.028475

Probability

No WH-initial WH-initial

No WH − Verb requirement (initial or not) WH − Verb (initial or not)

Subordinate clause: VSO Subordinate clause: V2 Subordinate clause: SVO Subordinate clause: SOV Subordinate clause: SOV and SVO

Participle − O O − Participle Participle − O and O − Participle

Relative: Category irrelevant Relative − Noun Noun − Relative Relative − Noun and Noun − Relative

Interpretation

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169

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5.8 Discussion: Grammar Compared to previous studies on Eurasian linguistic typology (Kortmann and Auwera 2011, Nichols 1992, Dahl and Koptjevskaja-Tamm 2001, Ebert 2001, Hock and Bashir 2016, Siewierska 1998, Dahl 2000, Plank 2003) our results both confirm earlier theories as well as give new insights about the grammatical geography of the area. Obviously, divergence, convergence, as well as parallel drift over time contribute to the typological diversity over the Eurasian landmass. There are some important observations, which have some bearing on our cultural constraints model, sketched in chapter 2. Further, the geographic extension, both of state combinations as well as clusters, give us valuable information on language contact, conservatism, and development. Following in the footsteps of an extensive literature on areal typology, manifested by large amounts of literature, handbooks (Haspelmath 2001, Kortmann and Auwera 2011, Hock and Bashir 2016) as well as data resources (Dryer and Haspelmath 2013, Bickel and Nichols 2002b), the most important addition of our grammar section is the inclusion of historical languages. Data from ancient languages provide us with valuable information about the diachronic development leading to the synchronic distribution of properties of grammar. Further, data from ancient languages are also valuable when it comes to improving evolutionary reconstructions (Carling, Larsson, et al. 2018, Cathcart et al. 2018). We will summarize and evaluate our findings and observations here. Individually and in groups according to type, grammatical features have their own paths of change, independent from lexemes, which are also involved in divergence, convergence, advergence and drift. This result is evident from our visualizations as well as from other studies based on our data (Cathcart et al. 2018), supporting the theory (cf. Martinet 1975, 30–38) that typological change is not consistent within languages, not even within systems (see 3.1). Rather, change is influenced, at an individual level, by a number of factors, which are both language-internal as well as language-external. Grammatical change is observed to be swifter than lexical change (Greenhill et al. 2017), something that may explain why border zones between language clusters may emerge in relatively short timespans, as we will see below. However, on the other hand, typological change is also constrained by time and geography, and results may give us important information about the absence as well as the presence of intense contact and parallel changes in the past, serving as a valuable complement to the investigation of lexical data. Beginning with the map visualizations by domain and feature (5.3–5.6) we notice several important differences between the investigated features and domains. These differences should be considered in relation to the spread of language families and branches (map 2). Some features build huge geographic blocks of grammatical homoplasy, in which a specific pattern becomes dominant over wide land areas, typically complemented by a different pattern being dominant in another area. Other features are more divergent; only local patterns, which sometimes coincide with family sub-branching (e.g., Romance, Germanic, Indo-Aryan), can be identified. Further, some patterns tend to be stable over time, where we find a consistent diversity in diachronic and synchronic maps, whereas others are more prone to change. To some extent, the identified patterns correlate with the features’ level of granularity in the data: a feature with more variants and more coded values reproduce a higher amount of state combinations, and with a higher amount of state combinations, a larger diversity is found. However, this explanation, which partly is an artefact of the way in which we code our data, does not account for most of the diversity found in the maps. Rather, the inherent nature of various domains and features explain the difference in the amount of diversity. We may identify two basic types: stable and drifty features. The drifty features can be divided into two: converging (homoplasious) and diverging (homologous) features. The outcome of stable and converging features are often similar: they tend to build large blocks of homogeny in geography. In general, an important difference between the outcome of stable, diverging and converging features are how they stick to family and branch boundaries; converging features bridge

5.8 Discussion: Grammar

171

over branch and family boundaries, and even, for some features, over grammatical zone boundaries (cf. 1.4). Stable features stick to family boundaries whereas diverging features stick to branch boundaries. The difference between the stable, diverging, and converging feature types is not sharp; rather, there is a floating transition with lots of exceptions, both at macro and microlevels. Further, the types are sometimes contradicting each other: converging features, which have patterns overlapping family boundaries, may show extensive temporal stability, and diverging features, which follow family and branch boundaries, may show extensive temporal instability. In principle, features of a grammatical domain correspond in the overall patterns. However, there may be important internal differences with respect to the inclination towards convergence or divergence. Patterns of word order, alignment and verbal morphology patterns generally indicate lower degree of divergence, whereas nominal morphology and tense indicate a higher degree of divergence. However, these patterns may depend on both stability, convergence, as well as divergence. There are sometimes noticeable differences between features of the same domain (word order, alignment, and verbal agreement), as well as between features of the same grammatical property but with a difference in, e.g., tense. An example is the alignment by nouns in present tense (map 3a–c) and in past tense (map 4a–c), where the latter is more divergent and the former is more convergent. Differences follow a hierarchical pattern and we assume that this difference is connected to factors such as morphosyntactic and typological frequency (Haspelmath 2008, 2006), (in some literature defined as markedness (Croft 2003, 1990). Patterns of more frequent categories are more converging (patterns bridge over family boundaries), whereas less frequent categories, e.g., simple past or subordinate clause patterns, are more diverging (patterns follow family boundaries). As an example, we may consider the general difference between the alignment patterns with present progressive and simple past (maps 3 vs. 4, 5 vs. 6, 12 vs. 13) Present progressive is more converging, simple past more diverging; likewise with the pronouns, where the difference between present progressive and simple past is even more pronounced than with the nouns. It is worth noticing that pronouns in general, when compared to nouns, are more converging, for instance in the alignment patterns of nouns (maps 3–4) versus pronouns (5–6), and in nominal case marking (map 8) versus pronominal case marking (map 9). In word orders we notice that main clause is more convergent than subordinate clause, even though the difference is small (20 vs. 21), noun-adposition more convergent than noun-adjective, which is more convergent than noun-possessor (15 vs. 16 vs. 18). In our data, morphological properties connected to the noun phrase are the most diverging ones. Here we have definiteness marking (map 11), nominal and pronominal case morphology (maps 8–9), and gender / noun class (map 7). Further, we notice that future tense typology (map 14) is diverging, whereas all verbal agreement patterns are converging (maps 12–13). Word order patterns are all converging, with slight differences depending on category (maps 15–26), and with one exception: the position of the question word (map 26), which is surprisingly divergent, but still converging: Basque and Caucasian share patterns with their respective neighbours. When the complete data set is analyzed by a synchronic cluster analysis (5.7.1), we see a different pattern emerge, compared to the individual feature maps. This gives us information about general tendencies in our data. When we analyze data together, we may identify different patterns that explain the emergence of clusters: the presence of languages in space and time. We have decided to cluster data, independent of language family, by the method of Structure, described in 5.7.1. Results from our test is given in fig. 6 and maps 27a–c. Considering the tree indicating pairwise mutual similarities of clusters (fig. 6, tree diagram of the 10 clusters), we notice a tendency: the clusters (marked by numbers 1–10) fall into three main sub-groups, one mainly eastern group, which also includes the ancient languages (clusters 3, 2, 7, 5) one central group, which includes Slavic languages plus Romani (cluster 10) and Medieval Germanic laguages (cluster 1), and finally a western group, which includes all Western European languages, including Greek (clusters 9, 8, 6, 4). One language falls out very distinctly

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Tab. 33a: Overview of clusters, interpreted as zones, based on the full data set (note that the numbers are generated by the program and have no relevance to similarities between clusters, see fig. 6 for a tree of pairwise mutual similarities between clusters). Name

Number

Languages

Location*

Period of formation*

Medieval Germanic 1

Gothic, Old/Middle High German, Middle Low German/Low German, Old/Middle Dutch, German, Swiss German, Old Saxon, Old Frisian, Yiddish, Old English, Old Norse, Old Swedish, Elfdalian, Faroese, Icelandic

Northern Europe

1–800

Central Indo2 Aryan/West Iranian

Indo-Aryan / Central: Hindi, Urdu, Punjabi, / Northsestern: Sindhi, Kashmiri, / Western: Gujarati, / Southern: Konkani, Marathi; Nuristani: Ashkun, Kati; Iranian / Eastern: Pashto, / Western: Kurdish Kurmanji, Kurdish Sorani.

South Asia

400–1000

Basque/Caucasian

3

Basque: East, West Basque; Kartvelian: Old Georgian, Georgian, Svan, Laz, Megrelian; Northwest Caucasian: Kabardian; Northeast Caucasian: Batsbi

?

?

Greek

4

Classical Greek, Middle Greek, Modern Greek

Greek Peninsula

–500–500

Ancient IndoEuropean

5

Sanskrit, Prakrit, Pali, Latin, Avestan, Old Persian, Hittite, Luwian, Tocharian A/B, Sogdian

Central/Eastern Europe

–5th–4th mill. BCE

Goidelic

6

Old/Middle/Modern Irish, Scottish Gaelic, Manx

British Isles

0–500

Central Asian

7

Indo-Aryan / Northern: Nepali, / Northwestern: Central Asia Khowar, / Eastern: Oriya, Maithili, Bengali, Assamese; Western Iranian: Baluchi, Gilaki; Nuristani: Prasun; Turkic: Uighur, Uzbek, Turkmen, Turkish, Karachay-Balkar

300–1000

Scandinavian

8

Swedish, Norwegian Nynorsk, Norwegian Bokmål, Danish

1000–1200

Romance

9

Romansh, Friulian, Catalan, Italian, Old Italian, Northern Old Portuguese, Old Spanish, Sicilian, Mediterranean Portuguese, Spanish, Sardinian, Provençal, Ladin, French, Walloon

4–900

Slavic

10

Old Church Slavonic, Old Russian, Croatian, Central/Eastern Serbian, Slovene, Czech, Polish, Russian, Europe Ukranian, Upper Sorbian, Latvian, Lithuanian, Romani Sinte, Romani Arli, Romani Kale, Romani Bugurdži, Romani Sepečides, Romani Kelderash, Romani Lovara, Romani Burgenland

4–800

Scandinavia

* Locations and dates are approximations.

from this tendency: the Basque languages in the Iberian Peninsula, which connects to the eastern macro-cluster. The results of the cluster test represent, like the maps, a measure of synchronic similarity, tested on languages of different time periods. They are only indicative of the processes that have produced these patterns. The ancient languages may be helpful to point this out to us, as well as the evolutionary reconstruction, which has been described in 5.7.2. We identify five types of grammatical zones, by means of which we explain our cluster results (table 33a–b) as well as the admixtures (table 33b) and the distances (fig. 6) between them.

5.8 Discussion: Grammar

173

Tab. 33b: Hybrid or border zones. These zones are defined as a number of languages which are adjacent in geography and which display an admixture component from one or several groups higher than 10 %. Name

Languages

Components

Location*

Period of formation*

Medieval Northwest Old Provençal, Old French (Medieval Germanic Germanic+Romance), Middle/Modern English (Romance + Scandinavian), Frisian, Dutch (all).

Medieval Germanic, Scandinavian, Romance

Western Europe/ Britain

8–1200

Brythonic

Cornish, Middle Breton, Middle Welsh

Goidelic, Romance

Wales, Bretagne

8–1200

Uralic

Estonian, Finnish, Hungarian, Northern Saami

Slavic, Central Asian

?

?

Balkan

Bulgarian, Tosk Albanian, Romanian

Slavic, Greek, Romance, Ancient IndoEuropean

Balkan

800–?

Northeast Caucasian

Kryz, Lezgian, Kwarshi, Kurdish Kurmanji, Kurdish Sorani, Modern Armenian

Basque/ Caucasian, Central IndoAryan, Frontier Indo-Aryan

Northeast Caucasus

800–?

Iranian

Middle/Modern Persian, Shughni, Parachi, Tajik, Prasun, Iron Ossetian

Unstable

Persia

100–?

Insular Indo-Aryan

Maldivian, Sinhalese

Frontier IndoAryan, Eastern clusters

Islands of Indian Ocean

800–?

* Locations and dates are approximations.

These zones are to be seen as an extension of the zone types suggested by Nichols (cf. Nichols 1992, 12–25, Nichols 1997). For further discussion on individual zones, compare also individual chapters in (Kortmann and Auwera 2011, Hock and Bashir 2016). 1. Spread zones. These represent areas where property types are spread over large areas, where the grammatical diversity is low and where properties typically build large and coherent blocks of similarity. Spread zones are caused by geography and form the basis for more fine-grained types of similarity, such as 3)-4) below. 2. Accretion zones. Accretion zones are areas of extraordinary topographic resistance, such as (in our data), Caucasus or the Basque country. For various reasons, language change is extremely slow and disparate, grammatical diversity is high and grammar properties come out as divergent in most aspects. 3. Historical development zones. These represent geographic areas, where languages, during a specific period of time (typically following upon a demographic or linguistic change, migration, or similar) are subject to consistent change, leading to similarity. Converging languages may belong to the same language family or sub-branch, resulting in a structural similarity. The cause of the similarity is mainly innovation, which may be either convergence or parallel drift. Examples in our data are Western Europe, Scandinavia and the British Isles, Central South Asia, Central Asia, Mediterranean. 4. Conservation zones. This concept target areas or niches where language change is restrained for periods and where change may be slower than in the surrounding environment. Conservation zones, which can be very restricted, can be a result of the spread of an earlier development area, where the earlier patterns have remained consistent, but due to an ongoing change in the environment, they have become isolated into conservation zones. Examples are Iceland, Dalecarlia, Central Europe, Greece, Persia, and Northern India.

174 5.

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Border or hybrid zones. This concept targets areas or zones, typically located at the borders between or at the frontiers of development areas, where we find languages that demonstrate a pattern of stable admixture (between two or three clusters), often spanning over several centuries. In our test, we define border or hybrid zones as a group of languages that are spatially coherent but which show a certain amount (> 10 %) of admixture from another cluster.

It is obvious that both our conservation areas and hybrid zones represent a historical reality, where languages have spread, converged, diverged, become conserved or admixed as a result of historical events as well as factors such as language shift, language contact, relocation, or isolation (Ramat 2012). We observe a very high degree of complexity and dynamicity in the creation of linguistic similarity and diversity. We notice that linguistic subgrouping, like areal proximity, is secondary. The explanation of observed patterns is often complex and multifaceted and goes beyond these parameters. Beginning with the Romance cluster (9) (table 33a, map 27), we can identify this as a development zone emerging at the collapse of the Roman Empire within the Western Roman Empire during the Migration period (4–800) (Kabatek and Pusch 2012). Within a couple of centuries, all languages of this cluster develop a significant typological distance to their precursor, Latin. Evidently (cf. 4.2.8), the changes that led to the development of the Romance languages were emerging in Late Latin (which is not present in our data). The Medieval Germanic cluster (1), which includes its earliest attested language, Gothic, emerges during and after the Roman period and the Migration period, located north of the Western Roman Empire, spreading all the way to the Faroe Islands and Iceland and, after a while, results in conservative niches in distinct areas of Northern Europe, namely Icelandic, Faroese, Elfdalian, German, and Low German. Later, upon the end of the Viking Age in Northern Europe and the Union period (1100–1600), the Scandinavian cluster (8) emerges out of this group. To a large part, English also ranges under this group. Another cluster is represented by the Goidelic group (6), emerging among the Insular Celtic languages in the British Isles during the Roman period, creating a distance to the dying Continental Celtic languages, which unfortunately are too fragmentary to compile typological data (Schmidt 1993). The Brythonic languages continue to change in contact with Romance, resulting in the Brythonic border zone in the Southern British Isles (see further below). The Western Germanic language Middle English develops within a short timespan (1100–1200) at a significant distance from the Medieval Germanic cluster (1) and becomes a Scandinavian/Romance hybrid language. Modern English continues on this path, becoming a mainly Scandinavian language with a Romance component. The source language of this impact on Middle English, Anglo-Norman, was a language close to Old French, which in turn comes out as a mixture between Ancient IndoEuropean (i.e., Latin), Medieval Germanic, and Romance. In distance trees, these four Western clusters, Romance, Goidelic, Scandinavian and Medieval Germanic, group together (fig. 6). Moving towards the east, we have the Slavic cluster (10), another historical development zone, emerging during the migration period (5th–8th centuries ACE) in Eastern/Northeastern Europe. Apparently, this cluster, which includes its earliest attest language, Old Church Slavonic, continued to be a stable and homogenous group with little change up to present day. The two modern Baltic languages of our data, Lithuanian and Latvian, range under this cluster as well. One Slavic language falls out, Bulgarian (which comes out as a mixture of the Greek and Romance cluster), being cut off from the Slavic area by the Magyar Migration into the Great Hungarian Plain (8–900 ACE), and a member of the Balkan Sprachbund. Romani languages in our data range under this cluster as well, something that indicates that the Slavic cluster was not just stable, both in space and time, it also managed to influence later incoming migratory languages, such as Romani. The traditional Balkan Sprachbund (Mišeska Tomić 2011) turns out as a hybrid zone with large heterogeneity, not as a cluster of its own, which would be expected, considering the fact

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that Balkan features are included in our data (but they are of course complemented by other, “non-Balkan” features). Serbian and Croatian stick with the Slavic cluster, Romanian with Romance and Greek, Bulgarian mainly with Romance but with admixture of other groups, Modern Greek in a cluster containing all languages of the Greek sub-branch (Classical, Middle and Modern Greek), and Romani dialects with Slavic, and Armenian and Albanian, as mixed. The Uralic languages of our data set come out as an admixture zone. This results need to be taken with a grain of salt, since we lack the bigger picture of the relation of Finnish, Hungarian, and Estonian to the remaining Uralic family, and with a larger set of Uralic data, it is possible that the position of these languages would have been more stable. However, it is interesting to note the strong component of the Central Asian cluster (also including Turkic languages) in the Uralic languages, of our data (see further below). Old Prussian, a Baltic language that became extinct in the 18th century, belongs mainly to the Medieval Germanic cluster but with a Slavic component. As mentioned earlier, Romani dialects stick with the Slavic cluster, which is surprising in several ways. We know that Romani chib, migrating from Central India in the 5–6th centuries ACE was heavily influenced by Greek (particularly in the grammar) during the 11–12th centuries ACE (Matras 2002, 196–199). Our results show little trace of this – Romani chib keeps a significant distance to both clusters with Indo-Aryan languages in them (Central Indo-Aryan and Central Asian), as well as to Greek. A likely explanation is that Romani chib, which was in contact with Slavic (Matras 2002, 22–25) during the period following the migration from the Greek Peninsula to Balkan/Central Europe (14–15th centuries), went through a period of swift structural change during this period, before relocating further to the north and to the west (15th–16th centuries). After this period, inflected dialects (all Romani languages in our data except for Angloromani and Scandoromani) remained stable, whereas mixed dialects (Angloromani and Scandoromani) continued a convergence process and became structurally almost identical to their matrix languages, English and Swedish (Carling, Lindell, and Ambrazaitis 2014). From the extended western group of clusters (9, 8, 6, 4), there is a considerable distance to the eastern group of clusters (3, 2, 7, 5). In general, the eastern group is more heterogeneous and hard to interpret, which partly may be explained by the lacunae in our data. Clusters do not follow sub-branches of family trees as they basically do in the west: both the Indo-Aryan and Iranian sub-branches are split up into two different clusters, and the results are puzzling both from the perspective of sub-branching as well as of geography (Masica 1991, 446–464). However, there are several trends that can be connected both to historical development areas and earlier migrations, as well as to very ancient conservation areas. We should mention the Basque/Caucasian cluster. This result is noteworthy and contradicts the notion of accretion zones as areas of high diversity (Nichols 1992, Nichols 1997). The program only measures similarity and distance with respect to the data that is present, and it is evident that in the case of Basque and Caucasian we are dealing with very ancient and stable (in terms of speed of change) typological patterns that predate the spread zone families, Indo-European, Uralic, and Turkic. The preserving of highly archaic typological structures over millennia results in a similarity in relation to the more swift-changing languages, which paradoxically explains their similarity in our results. The similarity of Basque and Caucasian in our data is confirmed by a test using another method of clustering (Manhattan distance values), which is published elsewhere (Carling, Larsson, et al. 2018). In our solutions (map 27a), three languages of the Northeast Caucasian family, Kryz, Lezgian, and Khwarshi, apparently have begun to change and demonstrate admixture with the Central Asian (7) and Central Indo-Aryan (2) clusters. Towards the east we have the Iranian admixture zone (see table 33b), which is composed of a conglomerate of Ancient Indo-European (5) and eastern clusters (2, 3, 7). In the east, we have two dominant clusters, splitting the Indo-Aryan, Iranian, and Nuristani languages of our data, but excluding all historical languages of these branches: the Central Asian (7) and Central IndoAryan (2) clusters. None of these clusters include any of the historical ancestors, indicating that

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they either have emerged after the definite extinction of the ancient languages, during the end of the first millennium ACE, or that they emerged from another cluster, which migrated into the area and successively impacted the present languages. The patterns are difficult to interpret from a historical point of view, but a possible theory is that we are dealing with two different area types: the fist is a distinct area, best represented by the Central Asian cluster (7), which was geographically and structurally distant from our ancient languages (5) but which later influenced several of their predecessors. The second is a more recent historical development area, the Central Indo-Aryan cluster (2). The Central Asian cluster, of which the Turkic languages are most representative in our data, probably reflects a historical continuum in Central Asia, which includes the Uralic languages, as well as the Turkic languages. Later, patterns of this cluster spread throughout the Iranian and Indo-Aryan frontier languages, starting from the collapse of many Iranian languages in the Iranian-speaking area, such as Scythian, Parthian, Sarmatian, Bactrian, and Sogdian, continuing into the migration period and culminating in the expansion of the Turkic language family (6th–12th centuries), which eventually lead to the death of many relic languages of the area, such as Tocharian, Bactrian, and Sogdian. The ultimate source of this continuum is hard to reconstruct based on our data, since we lack a large number of crucial languages of the Uralic, Turkic, Tungusic, and Mongolian families. The distance in our solutions between the ancient languages of the Iranian branch, Sogdian and Old Persian, to Middle Persian and Modern Iranian languages supports the theory of a swift change. The fact that Tocharian shows almost no impact from the Central Asian cluster (7) is also noteworthy, since Tocharian is considered to be typologically and morphosyntactically distant from Indo-European and more similar to Turkic and Uralic (Carling 2017b, Schmidt 1982). The Central Indo-Aryan cluster (2), on the other hand, may represent a historical development area, which emerged in the Indian subcontinent in closer contact with Dravidian languages (Masica 1991, 34–50). However, this proposal needs to be supported by more data, in particular from Dravidian languages. The heterogeneous picture among the eastern languages in our results is likely a result of a number of dynamic linguistic and historical networks, caused by the complex geography of the entire region. Finally, we have the distinct ancient Indo-European cluster (5). It is astonishing that the languages of this cluster, with a few exceptions, such as Classical Greek and Gothic, give no or very little indication of splitting up into other clusters. Partly, these languages represent pieces of a complex and dynamic linguistic landscape that existed thousands of years ago. However, the cluster also likely represents the result of an development area, which was established by the migration and settlement of Indo-European languages in various phases and places during the Chalcolithic period, spreading from Eastern/Central Europe and towards the east and west (cf. discussion in chapter 7). After a while, this migration resulted in several conservation zones, such as the medieval Tocharian and Sogdian languages, which are considerably distant from languages such as Hittite, Luwian, and Avestan, in both time and space. As we notice from the evolutionary reconstruction (5.7.2), many of the specific characteristics of this cluster (nominative-accusative alignment in present progressive and simple past, both by nouns and pronouns, synthetic nominal morphology including a case system with nominative, accusative, genitive, dative, and peripheral cases, a three-gender system, case inflection on heads and modifiers in NPs, synthetic verbal morphology with full agreement on verbs in present progressive but not in the simple past, and left-branching word order) are features that we also can reconstruct to ProtoIndo-European. Further, this cluster gives important information about later development areas. Compared to languages such as Latin, Old Persian, Sogdian, Prakrit, and Pali, still spoken at the beginning of the 1st millennium ACE, the successors become quickly very distant to their phylogenetic ancestors – a result that has several implications. First, that grammar, i.e., linguistic typology of the type that we have investigated, may change rapidly: maps can be redrawn in a couple of hundred years. Second, that geography plays an important role in this change, but its role cannot be predicted. Finally, that the migration period (4th–8th centuries ACE) comes out as very important in reshaping the linguistic map of all of Eurasia, both in the west as well as in the east.

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Figure 8a: Timeline of number of gains and losses of Indo-European languages in the grammar data, using a strict clock, which allows rates to vary stochastically from branch to branch (Felsenstein 2004) and a gain-loss (probabilistic, Bayesian, MCMC, character-based) model, where the likelihood of the tree is the product of all branch likelihoods and branch likelihood equals probability of descendant state, given a) most likely ancestral state, b) branch length, c) gain parameter, and d) loss parameter (Cathcart et al. 2018).

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This interpretation is supported by an analysis of the temporal distribution of gains and losses, based on our Indo-European data. We display the reconstructed change events (gains and losses) of the evolutionary reconstruction model described in chapter 5.7.2 on a time-line (fig. 8a). The graph is based on reconstructed gains and losses between states, and should be seen in contrast to the unequal amount of documentation in our data (fig. 8b). From the result, we notice a highly

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uneven pace of change. The graph indicates four independent peaks of increased change during a 6,500-year span (from Proto-Indo-European to present). The first peak, which is relatively weak, appears during the 4th millenium BCE, coinciding with the early Chalcolithic and the migration and spread of most Indo-European branches. The second peak appears in the mid-2nd millennium BCE and coincides with the Late Bronze age, the beginning of the decline of the Bronze Age, which lead to a collapse of cultures (such as Hittite, Mycaenean) and language death. A third peak appears at the end of the Iron Age, during the late 1st millennium BCE, and finally we have the most important peak: the Migration period (5th–8th ct. ACE), where we also observe a new pattern of change: losses are more frequent than gains. This latter peak mirrors the almost complete reorganization of the linguistic map, that we also see traces of in our Structure test (5.7.1). How should we interpret the fact that the ancient Indo-European cluster (5), in distance trees, tends to group with the eastern languages rather than the western? This has potentially consequenses for the discussion on the location of the Indo-European proto-homeland (Pereltsvaig and Lewis 2015, Heggarty 2015, Mallory 2013), proto-homeland chronologies (Chang et al. 2015, Bouckaert et al. 2012) as well as migrations of Indo-European tribes and the preservation of structural features (see chapter 7). Likely, the eastern area represents a a conservative zone, against which the the western development clusters, Romance (9), Scandinavian (8), and Goidelic (6), as well as Greek (4), stand out as more swiftly changing, also in contrast to Medieval Germanic (1) and Slavic (10). As discussed already at the beginning of this volume (chapter 2), grammar per se, except for under specific circumstances, does not give specific information about sociocultural history. Here, lexical data has a much higher capacity of providing us with information on conditions of reconstructed periods. However, grammar conveys important information regarding previous contact, parallel drift, divergence, and isolation – more than, e.g., basic vocabulary, which basically conveys a history of split and divergence of languages. Our grammar data reflects a long period of development and gives us vital information on past contact and joint development between languages. These problems will be further discussed in chapter 7.

6 Atlas: Lexicon 6.1 Lexicon: feature organization and coding 6.1.1 Introduction The lexicology subsection of DiACL is a comparative lexical cognacy database, fulfilling the demands of phylogenetic, evolutionary, and lexicostatistical analysis but also accounting for information retrieved from the comparative method, such as external/internal reconstruction, relative chronology, and semantic change. These methods are substantially different in the way they investigate lexical cognacy and change (cf. 3.4). The most commonly used data type for phylogenetics and lexicostatistics is lexical data sets with basic vocabulary (Swadesh lists, Leipzig-Jakarta lists). Even though the lexicostatistical model serves as a basis for our methodology of coding, we are not specifically dealing with basic vocabulary here. Basic vocabularies are included in our database, and we use of basic vocabularies for evolutionary reconstruction. The basis for lexicostatistics is the measuring of rate of substitution of cognates of a predefined set of lexical concepts (Swadesh 1955, Dunn 2014, 193–194), a method that tabulates pairwise distances between languages, based on cognacy (see 3.4). An important criterion for inclusion of cognates in a list is that the semantic criteria match: if a cognate changes its meaning, it is excluded from the list. Since our aim is to create data sets, which are pre-prepared also for phylogenetic (lexicostatistical) analysis, it is a demand that these criteria can be fulfilled. However, our aim is also to compile data sets that meet the demands of lexicography and comparative linguistics, to which a lexicostatistical data set represents a significant reduction of a very complex and dynamic reality. First, we intend to include, as far as possible, dictionarytype information about lexemes (transcription, script, IPA, polysemy, grammatical information, sources, see fig. 4), as well as etymological information, i.e., various types of cognacy relations to other lexemes within a language family. However, we also intend to address the uncertainties and problems connected with the etymological method, in order to provide reliable and secure data sets, which are grounded in reliable etymological reference literature (see appendix 4b). As mentioned before, the database contains basic vocabulary lists (Swadesh lists), but lexical data is also expanded beyond the domain of basic vocabulary, into other domains of the lexicon. This is particularly challenging in the case of lesser-researched languages, such as languages of the Caucasus, where we have compiled lexical data, by means of fieldwork for languages that lack adequate dictionary resources. At the center of the Lexicology subsection of DiACL are lexical concepts or core concepts, a frequently occurring notion, used in comparative, contrastive and computational semantic research and data compilation (List and Cysouw 2016). Concepts are typically organized by concept lists or concepticons, defined as ‘curated sets of concepts, minimally indexed via one or more words from a language, but perhaps, also more elaborately described using multiple languages’ (Poornima and Good 2010). The concept list or concepticon model, as it is used by, e.g., the databases Intercontinental Dictionary Series or by Concepticon (List and Cysouw 2016) has its roots in the model introduced by Buck (Buck 1949), which only targets one family, Indo-European. However, the aim of our database is mainly comparative and diachronic, and therefore we have selected a model of chunking lists by area and family, which is different from a lexical database such as Concepticon. As described under 3.4, etymological reliability can be a complicated issue (Hoffman and Tichy 1980). In general, deep-family etymology and paleolinguistic speculation is not desirable, but the exact definition of a secure etymology is not set. A vast number of etymologies boil down to an uncertain origin, where no reliable reconstruction is possible. Due to their apparent correspondence in sound structure and meaning, these etymologies cannot be overlooked or regarded as pure coincidence. Here, we may think of multiple poshttps://doi.org/10.1515/9783110367416-006

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sible explanations, such as prehistoric migration words, loans, or substrate influence. We do not by principle connect these items to a non-attested substrate language (Kroonen and Iversen 2015, Vennemann and Noel Aziz Hanna 2003) or assume any specific direction of the borrowing, as is often the case in paleolinguistic literature, based on various arguments (e.g., assuming a specific prototypical structure of a proto-language, where certain etymologies do not fit). Holding the view that the languages of hunter-gatherers, or even the early Neolithic farmers, represented a diversity of families and isolates, in Eurasia just as in, e.g., South America, we stick to familyinternal reconstructions in lexical data. The unrelatedness of Eurasian isolates, such as Basque, Caucasian families, Etruscan, Sumerian, or Hattian, provide a strong argument in favor of a high diversity predating the large, migrating families, i.e., Indo-European, Uralic, and Turkic. On the other hand, we do not deny the potential occurrence of previous (substrate) linguistic material in our data. We are also attracted by the theory of ancient convergence areas (Gamkrelidze and Ivanov 1984), where lexemes and concepts may have been distributed, borrowed, and migrated over language boundaries in prehistory. The ultimate source of these borrowing may be difficult to reconstruct, in particular if we consider very ancient borrowings, i.e., at the state of protolanguages. A fundamental problem has been to solve this dilemma of ancient language contact and the uncertainty of etymological proposals in the database construction, in order to match the database design to our approach. For that purpose, we make use of a concept ‘Stub language’, which we apply in order to to connect lexical etymologies of concept lists. Stub languages, consisting of stub lexemes, are defined by Word lists and belong normally to a family, indicating that lexemes are connected both by concept and by etymology. Stubs connect lexical trees and may contain reconstructed forms, such as reconstructed roots, verbs or nouns (Pokorny 1994, Rix and Kümmel 2001), but they may also contain just a lexical meaning and a number, in case no proper reconstruction is preferred. They normally lead, in the next step, to proper reconstructions – of which there may be several – in proto-languages, such as Proto-Indo-European. In some cases, this reconstruction is merely a stub ‘proto-form’, indicating that no reliable comparative reconstruction can be done to a proto-language (e.g., in case of migration words, suspected substrate words or uncertain etymologies). Stub languages fill two functions: they keep toghether lists of various kinds (e.g., Swadesh lists, Culture lists), enabling downloading of lists for analysis, and they serve as a basis of cognacy, a node that keeps cognacy trees together. Examples are the etymological trees for Indo-European and Caucasian bear (fig. 10ab), which illustrate how stub languages and stub lexemes are used. For how this is solved technically, see 6.1.2. In the database, we make the following distinctions (fig. 4): Word Lists correspond to predefined lists of lexical concepts, such as a Swadesh list or a culture list from a specific area. For a description of motivations for compiling these lists, see 6.2. Word List Items (e.g., ox, wheel, blood) includes lexical core concepts as defined in the literature (Haspelmath and Tadmor 2009), corresponding to Concepts in the databases such as Concepticon (List and Cysouw 2016). A Lexeme connected to a Word List Item is typically a prototype concept (Geeraerts 2010, 65–70), which targets the first/main meaning in a language, but if there are two or several meanings in a language for a lexeme, we include all meanings. We have been inclusive in our selection of lexemes, also involving specialization (see table 35). Due to the principle of etymological coding, which organizes lexemes according to etymological trees, Word List Items may be connected to lexemes for which the meaning is changed in various ways (providing that there is a connection to a lexeme that possesses the Word List Item meaning). An important aspect for further computational analysis involves the filtering principles of semantic change, which will be described more carefully under 6.3.2. Etymologies connect lexical cognates inside the database and and can account for all types of complex relations between lexical cognates, including borrowing, derivation, and semantic change. The correlation between Word List Items and Etymologies can be seen in fig. 9, exemplified on a well-known etymology, the Indo-European word for blood/meat. The organization of Word List and Etymology parts in the database will be described more in detail under 6.1.2.

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Figure 9: Graph explaining the difference between the lexicostatistical cognacy method and etymology method of comparative linguistics: in lexicostatistical cognacy blue circles and red circles belong to two different cognacies, blood versus meat, in the etymology method all circles belong to one tree.

6.1.2 Cognacy coding and etymology coding For analyzing and visualizing lexical data, we define two types of coding, which in our database are reflected by the structure of the etymological trees of lexical concepts. The first method, labeled cognacy coding, corresponds to the lexicostatistical coding method, the way in which it was designed by Swadesh and his followers in the 1950s (Swadesh 1952, 1955). There is a rich literature on advantages and problems of the lexicostatistical method, and there are different views, e.g., on whether synonyms should be included, or if only one single lexeme per lexical concept is allowed in a language, how to treat semantic matches, and how to define cognacy precisely (Chang et al. 2015, Pereltsvaig and Lewis 2015). For Swadesh lists in the database, we stick to a traditional method, which means that we keep cognacy within the semantic field of the lexical concept, we exclude loans, but we allow for polymorphism (i.e., including more than just one lexeme per language), if lexemes represent the targeted slot of the lexical concept. The coded cognacy is entirely flat: we do not build etymological trees with Swadesh vocabulary data. All lexemes of a cognacy tree are, on equal terms, drawn back to a node, which is either a reconstructed form of a proto-language (e.g., Proto-Indo-European), or a stub (i.e., a node without a reconstruction). Lexical reconstruction by the comparative method – a discipline known as etymology – is very complex and often, the origin of etymologies cannot be verified with certainty. To be able to distinguish words that have secure etymologies from words that are clearly cognates but which cannot be reconstructed with certainty to a proto-language, we connect lexemes of etymologies by stub languages, which have been more carefully described in 6.1.1. In this context, stub nodes of stub languages represent headings of lemmas in an etymological dictionary. These stub nodes, which have a unique ID number in the database, are also the basis for the etymological lemmas in Appendix 3b, which lists all lexemes (cf. fig. 10a–b). For the so-called “culture lists” of our database, we make use of a coding system, which reflects a historical-comparative model rather than a lexicostatistical model. We label this etymology coding. Etymology coding is more complex than lexicostatistical cognacy coding: cognacy coded data sets can always, by means of filtering (see 6.3.2), be extracted from etymology coded sets – but not vice versa. The culture data sets make full use of the etymology function of the database. Basically, the etymology coding is based on core concepts in combination with etymological trees, which include all changes, including meaning change, lexical derivation, and borrowing that occurs in etymological trees. The basic principle for inclusion in trees is to include derivations as long as the extended concept meaning (e.g., concept meaning including conceptclose specializations and generalizations, see 6.3.2) is kept, or to include semantic change as long as the basic derivations (root + stem) are kept. I.e., if the core concept is bull, the etymolog-

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Figure 10a: Etymological tree of the Indo-European words for BEAR, from the database DiACL.

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ical trees attached to this core concept are those in which a substantial part of the lexemes of the tree have kept the core meaning bull. If there is a meaning change in a language, which is not caused by a morphological derivation (e.g., compounding), the lexeme is still attached, both to the etymological tree as well as to the core concept bull (the meaning change is reflected in the Meaning field of the lexeme). On the other hand, if there is a morphological derivation of a word (e.g., from another root or lexeme), but for which the meaning is bull, the word is also included. All types of occurring relations, derivation (both verbal and nominal), borrowing, inheritance, or uncertain origin, can be mirrored in the etymology (fig. 9, 10a–b). The result of this coding model are conglomerates of etymological trees, clouding around core concepts, e.g., concepts targeting prototype meanings (table 35), including smaller and larger semantic deviations as well as etymological and semantic links to other core concepts. We have selected this model for a purpose: a reduced lexicostatistical data set can always be retrieved out of these conglomerates (by means of the filtering coding), but these conglomerate trees, which more carefully reflect etymologies retrieved by the comparative method, can never be filtered out of a lexicostatistical set. The outcome is also highly interesting: changes in meaning and derivation can be followed over trees, illustrating the enormous richness and complexity of lexical change (fig. 10a–b).

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Figure 10b: Etymological tree of the Caucasian words for BEAR, from the database DiACL.

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6.1.3 Lexemes: core of the subsection Lexicology Lexemes constitute the core of the DiACL Lexicology subsection (see fig. 4). Lexemes are given for both attested (contemporary and historical) and reconstructed languages (see fig. 10a–b). In the case of reconstructed languages, lexemes are given with an asterisk (*), as usual in comparative linguistic literature. Further fields in the Lexeme table are Transcription, which gives the transcribed form of the lexeme in Latin script (see 1.6 for orthographic conventions), and Script, which gives the form of the native writing system. This distinction is valid for languages with non-Latin writing systems. The Meaning field targets all meanings of a lexeme, not just the connected lexical concept (Word List Item, e.g., eel, book, bull). In this field, polysemous meanings that are substantially different are distinguished by a semi-colon (;) whereas meanings that are synonymous are distinguished by comma (,). Meanings in the database stick to dictionaries, but for the purpose of various semantic analyses in this book (6.3.2.−6.3.6), we have conflated and simplified the meanings. Thereupon, a field for Grammatical data is given. This field gives information about whether the lexeme is a verb or and adjective. For nouns, the gender of words is given.

6.1.4 Word Lists: functional hierarchies of lexical concepts Lexical data of the DiACL subsection Lexicology is organized into semantic taxonomies, labeled Word Lists, which can be described as a system of organizing lexical concepts into functional and environmental hierarchies. The hierarchical system is not implemented in basic vocabulary (Swadesh lists), which are not distinguished or sub-classified by geography and have a flat hierarchy (6.1.2). The design of the database follows a basic model where linguistic features (lexical and typological) are organized into hierarchies. The main levels are more general, typically a geographic area or a family and a list type (grammatical, lexical) but the lower levels contain a higher degree of granularity and geographic adaptation (see fig. 11). For instance, in the grammar section, there is a dataset Typology/Eurasia (see previous section of this book). In the Lexical section, the corresponding languages of the Typology/Eurasia dataset are split into several different lists: Culture list Indo-European, Culture list Caucasian, Culture list Turkic, Culture list Uralic. The next level is Word List, which targets a specific type of domains of lexical concepts, which are adapted to a geographic area. These geographically adapted lists, which we label “culture lists”, aim at compiling lexemes, which we assume to have a high functionality and which still reflect the dynamics of geography, ecology, and subsistence of languages and language families of the area (see 6.2.2).

Indo-Eu uropean Culture e Vocabu ulary

Wo ord List:

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Figure 11: Organization of Word Lists (lexical concepts) in the database DiACL.

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6.1.5 Organization of etymologies Lexical data is organized by etymologies. The etymology function of the database allows a higher degree of coding granularity than normally found in lexical cognacy databases. Here, a Lexeme can be linked to any other Lexeme within the database (also of other families); either as Ancestor Lexeme or as Descendant Lexeme. Then, the nature of the connection can be specified by means of seven different definitions: Unspecified / Inherited / Probably borrowed / Certainly borrowed / Uncertain origin / Wanderwort / Derivation. Unspecified means that the etymological relation has not yet been processed within the database, an indication that there is a cognacy relation (not a loan or similar). Inherited means that there is a certain cognacy relation between an ancestor and descendant lexeme, which is not altered by morphological derivation (e.g., compounding, suffixation). Probably borrowed means that it is likely that the descendant lexeme is borrowed from its ancestor lexeme. Certainly borrowed means that the descendant lexeme is borrowed from its ancestor lexeme. Uncertain origin means that the lexeme has some correlation to an ancestor lexeme (i.e., the similarity on form and function is too close to be mere coincidence), but the exact relation is uncertain, and a number of alternatives might be possible, such as early loan, sound symbolic change, or analogical influence from other words. Wanderwort means that the word that has undergone multiple borrowing events, and our ability to determine the ultimate source, direction or vehicle of transmission is either secondary, or, in cases of very ancient wanderwörter, impossible to reconstruct (Haynie et al. 2014). Derivation means that the lexeme has a form which is marked by morphological derivation in relation to its ancestor lexeme. Derivation includes all kinds of derivational morphology that change the form (and function) of a lexeme, e.g., pre-, in-, and suffixation, ablaut, or compounding. The inclusion of compounding means that a specific lexeme, if composed of two or more lexical roots, can be part of two or more etymological trees. In the data set of the current atlas, the relation Derivation has been used to mark language-internal derivations, such as in the chain (see Appendix 3b) Lat tardatiōne ‘arriving late’ (83326) > (Inherited) Catalan tarda ‘afternoon’ (83328) > (Derived) Catalan tardor ‘autumn’. In this chain, tardatiōne and tarda are filtered out as ‘meaning change’ (see 6.3.2).

6.1.6 How to deal with etymological reliability and macro-etymologies The discipline of etymology, though capable of yielding precise information about conditions of a reconstructed past and therefore highly important to comparative linguistics, nevertheless engenders difficulties and uncertainties (cf. Mailhammer 2014, Schuhmann 2017). Its aim is fundamentally diachronic, but all results of reconstructions are potentially affected by horizontal activities, operating in a past synchrony. In the process of reconstruction, if assuming far-gone semantic change, occurrence of sporadic sound change, leveling, and/or prehistoric language contact, the discipline of etymology may be connected to great uncertainty. Our policy is to use etymology in a very strict sense, meaning that: – We put meaning and function before form in judging etymological reliability; – We are very hesitant about macro-etymologies (i.e., etymologies using capitals such as N, V for indicating “vowel of some value”, “nasal of some value”); – We are very hesitant about postulating prehistoric horizontal processes, such as loans from an unknown substrate language, or early borrowing between reconstructed states, in particular if the source language is unknown. However, it is sometimes necessary to make decisions on cognacies between lexical concepts, shared within a family or an area, even though the details of transfer remain unclear. As de-

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scribed under 6.1.2, we use stubs at the root of etymological trees. Stubs are mainly familyspecific, but we may, in these stub lexemes, indicate connection to other stubs of other families. We also frequently make use of the notion “proto-form” (cf. Kroonen 2013), to indicate the absence of a proper reconstruction or the presence of a cognate also in other families, which cannot be certainly identified as a loan in one or the other direction. As an example we may look at the root for ‘oats’, Latin avēna ‘oats; stalk, straw’, which can be reconstructed as Proto-Italic *aweksnā- ‘oats, straw’ and which it is paralleled in Balto-Slavic, e.g., Latvian àuzas ‘oats’ (appendix 3b, 74239). To some researchers, the lexeme is believed to be a non-Indo-European substrate word (Lubotsky et al. 2010, Vaan 2008), whereas more traditional explanations, such as (Walde 1910, Walde and Hofmann 1965) instead propose an internal IndoEuropean origin, e.g., Latin ovis ‘sheep’, PIE *h₃éu-i- ‘sheep’ (as in the Germanic oats-words, Icelandic hafrar, Swedish havre, from PIE *kapro ‘buck, he-goat’), or, alternatively, a relation to Sanskrit avasám ‘nourishment’. In this case, we trace the tree of Proto-Italic *aweksnā- ‘oats, straw’ (and its daughters) and Balto-Slavic *awiź-, *awiś- ‘oats’, and its daughters words back to a Stub node by the description PItal *aweksnā- ‘oats, straw’ (substr.?) (appendix 3b, 74239) (Vaan 2008). Another example is the Caucasian root for bear (fig. 10b). In this case, and in several other instances of our data, we find that lexemes of the three Caucasian families, Kartvelian, Nortwest Caucasian, and Nakh-Dagestanian, share similarities in form to an extent that a common cognacy is highly likely. We leave the discussion on genetic relationships between these families open; nevertheless, in case such as these, we derive the lexemes back to a Stub node (see earlier discussion on Stub nodes and Stub languages) with a cognate ID (see also appendix), pointing out the cognacy, but without attempting a reconstruction of a joint proto-form. The ultimate source of the cognacy may be very early migratory words or early genetic relationship between these families.

6.2 Culture vocabularies: aim and definition 6.2.1 Aim of the culture vocabulary atlas The current book puts much focus on sociocultural reconstruction, and for this purpose, we compile “culture vocabularies”: lists of lexical concepts of a known high age and high cultural salience. We expect these lexemes to have a change behavior that is partly different from both basic vocabulary and grammar. There are potentially many aspects of interest here, something that has influenced our coding (cf. 6.1.4, 6.3.2). The first and most important aspect is the geographic distribution of words, and in particular etymologies, i.e., lexemes that have shared ancestry by cognacy. In our definition, “etymology” involves both semantic change, loan, and morphological derivation (see 6.1.5). This results in “etymologies” being highly complex conglomerates of various associations between lexemes. Contrary to basic vocabulary coding, our aim has been to be as inclusive as possible in etymology coding. We want to follow all possible changes of lexemes; including derivations, splits, borrowing, semantic change (as well as loss) that culture words may undergo during their history. This has been the basis for the selected etymology coding system, which is more carefully described in 6.1.2. We are potentially interested in three aspects of lexical change of culture words. The first is borrowability, which refers first to the degree to which a specific concept is borrowed from a foreign language. Here, our interests go deeper: we also want to know when, from where and why words are borrowed. Are there any cultural or historical implications? Are there changes in subsistence, or other factors, which cause words to be borrowed? We are also interested in stability. Are there words which are seldom or almost never borrowed? Do some words remain stable, generation after generation, over millennia, and hence become distributed over large areas? Is there a connection to which concepts these words represent? Does this stability have cultural

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connotations, meaning that some cultural concepts are carried along and spread over large areas, either by relocation of speakers or by introduction of novel concepts? Second, we are interested in cognacy. Do some concepts form stable cognates, which remain unchanged and are spread over large areas, whereas other concepts form rich and complex cognate trees, with abundant derivations and a number of mutual relations? Reversely, are some cognates restricted, either locally (between closely related languages) or between distant languages, forming highly restricted trees? Further, do some concepts engender a multitude of cognates, whereas other concepts only have a few, looking over the family trees? Is there any connection between cognacy and sociocultural salience, with implications for stability, functionality, and affordance? Finally, we are interested in semantic change, or, reversely, the absence of semantic change of words in relation to their concepts. Are there any general principles for colexification and semantic change of cultural concepts? What do colexification and semantic change tell us about the cultural connotations, such as functionality, affordance, superstition, or taboo, of specific concepts? Is semantic change of cultural concepts regular, or can we identify unpredictable changes in the data? These are all complex questions, and we admit that we are not capable of answering them all. In our data, the Indo-European and three Caucasian families are best covered when it comes to cognacy. Languages from other families, where we have mainly targeted languages that are geographically adjacent or included in our area, have either not at all been covered for cognacy (Basque, Semitic), or they are not completely covered for cognacy (Uralic, Turkic) (see appendix 3b).

6.2.2 Motivation for selection and classification of concepts of the atlas The approach behind our model for organizing lexical concepts into hierarchical systems has been described under 6.1.4. Here, we will motivate the selection of the current atlas. We aim at concepts with high stability and age, with a bearing for subsistence from a deep historical perspective (Carling, Cronhamn, et al. 2018, Carling 2013, 2016). We aim at compiling culture lists that reflect stability and change both language-internally as well as areally. Methodologically, semantic taxonomy (Buck 1949), as well as borrowability by semantic category (Haspelmath and Tadmor 2009, Tadmor and Haspelmath 2010) are important prerequisites to our selection. As for semantic taxonomy of culture vocabulary, we use a matrix of cultural main categories, which is divided into hierarchically organized features, by geographic area and language family. At the following macro-area-adapted level in the hierarchy, culture lists contain lexically generic meanings, which are selected according to geography and environment, relevance to subsistence system, cultural function or affordance, and occurrence in reconstructed vocabularies of language families, where we have basically leaned upon Indo-European reconstruction (Campbell 2013, 346,ff., Mallory and Adams 2006, Gamkrelidze, Ivanov, and Winter 1995, Gamkrelidze and Ivanov 1984). We focus mainly on subsistence, and our aim has been to identify the concepts representing the words for the most crucial subsistence innovations of the first and second revolutions, namely the Neolithic Revolution 10,000–11,000 BP, when farming first emerged in Anatolia and the Fertile Crescent, and the Secondary Products Revolution 6,000–7,000 BP, which lead to many important innovations such as traction, milking, wheel, and plough (see 6.6.1, 6.11). The aim is to provide a weighed selection, representative for quantitative analysis, aiming at responding to the research questions listed in the previous chapter. However, we are fully aware that our decided list has shortcomings in terms of concepts that should have been included as well as concepts that should have been excluded. Other very important domains of culture, such as kinship and social structure (Jordan et al. 2009, Nikolayeva 2014, Fox 1983, Hettrich 1985), should have been included in our data set as well, but the main reason for excluding these groups has been time and resources: we preferred to have a more thorough coverage on the selected cultural domains.

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Tab. 34: List of thematic groups in the atlas and their corresponding OCM Subject category number (Murdock et al. 2008). Atlas main category

Atlas subcategory

OCM main category

OCM subcategory

Hunting and trapping

Game Predator animals Predator birds

220 Food quest

224 224 224, 223

Animal husbandry

Domestic animals Pet animals Domestic insects Pig raising Bovine cattle and dairying Pastoral activities Poultry Animal products Wool production

230 Animal husbandry

231

Agriculture

Land use Tillage Cereal agriculture Vegetables and arboriculture Textile agriculture

240 Agriculture

241 241 243 244, 245 248

Food preparation

Food preservation Drink and drugs

250 Food processing 279 Drink, drugs, and indulgence

251 273

Leather, textiles and fabric

Skin and fur production

280 Leather, textiles, and fabrics

281

231 231, 234 233 235 237 236

Textile production Processing of basic materials

286–287

Trees, lumbering and woodworking Metallurgy

320 Processing of basic materials

322

Weapons and warfare

Weapons and warfare

720 War

726

Transportation

Draft animals Vehicles

480 Travel and transportation

492 493

Numbers and measures

Ordering of time

800 Numbers and measures

805

325

For Eurasia, we have independent concept lists for all families in the database. This is primarily due to cognacy, since lexemes are mainly connected by their families. However, loans and migration words typically cross over language family boundaries. The available word lists, which differ slightly between the families, are listed in appendix 3a. The lists are principally overlapping, with a basic list of around 100 concepts (table 35). In our selection of cultural concepts, we focus mainly on subsistence concepts. Following previous classifications of cultures by subsistence (Lomax et al. 1977, Murdock 1969, Kirby et al. 2016), the ethnographic classification group in focus for the culture vocabularies of Eurasia are mainly plow agriculturalists (Lomax et al. 1977, 665 ff). This encompasses several ethno-linguistic sub-groups within the languages of our database, mainly plow agriculture / Indian tribal (extensive agriculture, no dairy), plow agriculture / East Asian irrigation (irrigation agriculture, no dairy), plow agriculture / Europe and plow agriculture / Middle East (intensive farming, diary). According to the main classification, important crops include grain, wheat, and corn; animal husbandry includes pigs, sheep, and bovines (most, but not all groups have dairy consumption); and the most important agricultural tool is the plow. This subsistence classification basically targets contemporary societies, but it has a history of emergence that spans over the past 10,000

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years. We have used the ethnographic classification (Lomax et al. 1977, Murdock et al. 2008) as a matrix for selecting and organizing concepts; we have also taken the reconstructed vocabulary into consideration, where we are most well provided with data from the Indo-European family (Schrader 1917, Mallory and Adams 1997, 2006, Fortson 2010). Our Caucasian material, which is partly based on new fieldwork and new etymological analysis, is adding a substantial amount of data here. Besides subsistence, kinship and marriage rules are also important for the ethnographic classification of cultures according to this model. Kinship and marriage, just as social structure, are not included in this atlas. In the DiACL database, we use a system of organizing concepts which is adapted to our data, which is different from the OCM (Outline of Cultural Materials) system (Murdock et al. 2008). The correspondence between thematic groups in the volume and the OCM subject category system is given in table 34. A complete list of our concepts and the coverage for each of the different lists (Indo-European, Caucasian, Uralic, Turkic, and Ancient Non-Indo-European) with the classification used in the database is given in appendix 3a. For this volume, we have re-classified the concepts according to the OCM standard and the internal colexification / meaning change of concepts, which we describe in 6.3.1. In table 35, we give the list of concepts with satisfactory coverage, organized according to their classification in the current volume.

6.3 Organization, classification and visualization of lexical data 6.3.1 Organization of chapters and classification of concepts In the coming chapters, we have used several methods to organize and classify our data. First, the OCM system (Murdock et al. 2008) has been used as a basis for organizing concepts and chapters (cf. table 34). Our atlas covers only a fraction of the subjects of the complete OCM index, partly due to our aim of covering only pre-colonial societies, our focus on concepts with a high age, and our main focus on subsistence items. However, we have also introduced a classification of the concepts, which is based on their behavior in colexification and meaning change networks, as well as their behavior in terms of borrowability, semantic instability, and cognacy productivity, three important metrics that we apply to our data (see 6.1.2 for the coding system and 6.3.5 for the statistics). Hence, the concepts are divided into main domains, representing chapters (such as ‘Hunting and trapping’ or ‘Animal husbandry’), which is divided into subchapters (such as ‘Game animals’ or ‘Pig raising’). Some chapters begin with a general description, others will move immediately into the subchapters. The text will first describe the cultural domain and subdomain in general terms, typically with a distinct focus on, at first, the earliest appearance of the domain, e.g., for ‘Pig raising’, the domestication of the pig in the early phase of the Neolithic revolution. The text gives an introduction to recent articles and advances within, e.g., archaeology and prehistory of the targeted domain. Thereupon follows a brief discussion on the cultural history of the domain, typically with reference to specific concepts, and often with reference to anthropological or historical literature. Thereupon, there is sometimes a discussion on the mythic relevance of the domain, or of specific concepts. After this brief overview come the maps and the graphs (see 6.3.2–5) of the thematically organized group of concepts. Finally, there is a discussion on the data and results, evaluating the concept maps, the meaning change charts, and the statistical evaluations. The most important difference between the order of chapters and the classification is found in the category products. In our text, we deal with the products of the various cultural activities under their respective chapter. However, in their classification, we put them together into two groups, agricultural products (labelled products) and hunting products (labelled materials). We will discuss these issues more carefully in 6.13.

to plow to sew to sow to spin (thread) to weave bull calf cattle cow flax grain (generic) oats rye wheat barley cat dog bee donkey horse ox mead wine bison deer hare rabbit wild boar knife saw scythe

ACTIVITIES ACTIVITIES ACTIVITIES ACTIVITIES ACTIVITIES CATTLE CATTLE CATTLE CATTLE CROPS CROPS CROPS CROPS CROPS CROPS DOMESTIC ANIMALS DOMESTIC ANIMALS DOMESTIC INSECTS DRAFT ANIMALS DRAFT ANIMALS DRAFT ANIMALS DRINK AND DRUGS DRINK AND DRUGS GAME ANIMALS GAME ANIMALS GAME ANIMALS GAME ANIMALS GAME ANIMALS IMPLEMENTS IMPLEMENTS IMPLEMENTS

6.6.3 6.8.2 6.6.3 6.8.2 6.8.2 6.5.5 6.5.5 6.5.5 6.5.5 6.6.6 6.6.4 6.6.4. 6.6.4 6.6.4 6.6.4 6.5.2 6.5.2 6.5.3 6.11.1 6.11.1 6.5.5 6.5.3 6.7.2 6.5.5 6.4.2 6.4.2 6.4.2 6.5.4 6.6.3 6.6.3 6.6.3

PREDATOR ANIMALS PREDATOR ANIMALS PREDATOR ANIMALS PREDATOR ANIMALS PREDATOR ANIMALS PREDATOR ANIMALS PREDATOR ANIMALS PREDATOR ANIMALS PREDATOR BIRDS PREDATOR BIRDS PREDATOR BIRDS PRODUCTS PRODUCTS PRODUCTS PRODUCTS PRODUCTS PRODUCTS SEASONS SEASONS SEASONS SEASONS SEASONS SMALL CATTLE SMALL CATTLE SMALL CATTLE SMALL CATTLE SMALL CATTLE TILLAGE TILLAGE TILLAGE TREES

bear jackal leopard lion lynx snake wolf fox eagle owl raven honey hops milk salt wax (bees) wool autumn harvest spring summer winter goat lamb ram sheep kid cultivated field furrow plow ash

6.4.3 6.4.3 6.4.3 6.4.3 6.4.3 6.4.3 6.4.3 6.4.3 6.4.4 6.4.4 6.4.4 6.5.3 6.7.2 6.5.5 6.7.1 6.5.3 6.5.9 6.12.1 6.12.1 6.12.1 6.12.1 6.12.1 6.5.6 6.5.6 6.5.6 6.5.6 6.5.6 6.6.2 6.6.2 6.6.3 6.9.1

Ch.

Word List

Classification

Word List

Tab. 35: List of cultural concepts of the atlas with satisfactory coverage. The classification below is based on OCM standard system of cultural classification, combined with the occurrence of colexification / meaning change of the data as well as the concepts’ behavior in terms of borrowability, semantic instability, and lexical cognacy. Note that the classification may differ slightly from the organization of chapters in the atlas in 6.4–6.12. Classification

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Ch.

190

IMPLEMENTS IMPLEMENTS MATERIALS MATERIALS MATERIALS MATERIALS MATERIALS MATERIALS METALS METALS METALS METALS PIG RAISING PIG RAISING POULTRY POULTRY POULTRY POULTRY

sickle spade meat leather fur grease stone wood copper gold iron silver pig piglet chicken duck hen rooster

6.6.3 6.6.3 6.9.3 6.8.1 6.8.1 6.7.3 6.9.3 6.9.3 6.9.2 6.9.2 6.9.2 6.9.2 6.5.4 6.5.4 6.5.7 6.5.7 6.5.7 6.5.7

TREES TREES TREES TREES WEAPONS WEAPONS WEAPONS WEAPONS WEAPONS WEAPONS WEAPONS VEGETABLES & FRUIT VEGETABLES & FRUIT VEGETABLES & FRUIT VEHICLES VEHICLES VEHICLES VEHICLES VEHICLES

beech birch elm oak army arrow axe bow shield spear sword apple grape turnip axle hub wagon wheel yoke

6.9.1 6.9.1 6.9.1 6.9.1 6.10 6.10 6.10 6.10 6.10 6.10 6.10 6.6.5 6.7.2 6.6.5 6.11.2 6.11.2 6.11.2 6.11.2 6.11.2

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191

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6.3.2 Categories of lexemes and data coding principles for statistical filtering In the following section of the atlas, there will be several types of visualizations, which organize lexemes by their meanings as well as by their connections to other lexemes in languages. Compared to the complete data set (appendix 3b), visualizations and statistical graphs are different, depending on what data they include or exclude. As described under 6.1, lexemes in the database are fundamentally organized according to etymological trees, which derive back to a common joint root, which we in the database label “Top node”, belonging to a “Stub language” (fig. 10a–b). However, the etymological trees of the database also include words that have been derived (but kept or expanded their meaning), words that have kept their morphological structure but changed their meaning, as well as words that have been borrowed. Hence, the etymological trees form the basis for all maps and graphs in the atlas, but for the purpose of the different visualizations, a filtering and recoding of lexemes has been necessary. Due to our model of compiling data, i.e., as etymologies, lexemes of the etymological trees represent a rich variety of different meaning changes, also including change of word class (e.g., verb > noun and vice versa). In lexicostatistics (see 3.2), the keeping of a concept’s core meaning is central for inclusion versus excluding lexemes from a set (Dunn 2014). Meaning change is important in our model as well, but we adapt a more fine-grained distinction to meaning change than is normally done in lexicostatistical research. We distinguish the following types (Geeraerts 2010, 26–42, Fellbaum 1998): a. Lexemes that have kept the core meaning (alone or extended by colexification) of the concept and which are inherited from a precursor (marking 1) b. Lexemes that have kept the core meaning of the concept (alone, or extended by colexification), but which are loaned (marking 2) c. Lexemes that have expanded or slightly changed (typically by specialization or generalization) the core meaning of the concept (e.g., stone > gravel, deer > doe), alternatively added a completely changed meaning by colexification (e.g., deer > elephant, deer), but which have preserved the original meaning as secondary, and words which are secondary in use (obsolete, dialectal), which are inherited, not loaned (marking 3) d. Lexemes like 3), but which are loaned (marking 4) e. Lexemes that have changed (more or less completely) the core meaning of the concept and lost the original meaning, typically by metaphor (e.g., wolf > criminal), metonomy (apple > apple tree, wool > gown), or change from activity to object (e.g., dig > spade) or vice versa (marking 0, not shown on maps and not used in statistics). First, we admit, that these distinctions are not always easy to make, but as a guide, we have applied a predefined set of rules. The distinction between 1–4 and 0 is straightforward: if the concept meaning (e.g., bull) corresponds to a word meaning (‘bull’) in a language, then it is a 1–2. We have made exceptions here, in order to “clean” the lists (Hoijer 1956, Chang et al. 2015): words that are marked as “dialectal”, “rare”, “obsolete” or “literary” we have automatically coded as 3–4, even if they have kept the core concept meaning: a coding 1–2 is supposed to fill the normal, default meaning slot in a language. However, the distinction between coding 3–4 (colexified, expanded, or slightly changed meaning, but with the core meaning kept) and 0 (completely changed meaning) is often difficult, and we have applied a set of guiding rules here. Colexifications with the original core meaning preserved (as secondary meaning, is coded as 3– 4. Metonymic and metaphoric changes imply that a lexeme is sorted as “changed” (0) (with the exception if the core concept is kept by colexification). Coding “extended” includes, e.g., changes in species, as long as they belong to the same close family, such as hyena > jackal (3–4), but not fox > cat (0). Further distinctions are product from produce, e.g., grain > bread (0), wax > candle (0), and important changes in physical and cultural form and function, e.g., turnip > rape (0), but turnip > beet (3–4) and turnip > root (3–4). Grammatically, verbs and nominali-

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zations (verbal noun, participle) are marked as “extended”, e.g., to sew and sewing (3–4), like noun and adjective, e.g., rain and rainy (3–4), whereas verbs and their resulting content object are marked as “change”, e.g., to plow and plow (n) (0). The coding has several purposes, of which the most important are filtering data for maps and statistics. A further distinction of importance is loan. In the database, as described under 6.1, a number of types of loans are distinguished, including “wanderwort”, “certainly borrowed” and “probably borrowed”. It has been necessary to conflate these distinctions, without losing granularity (which is preserved in the database), and the coding therefore distinguishes inherited (1 and 3) which includes inherited words with proper etymologies as well as words which are very early migration words or very early borrowings, i.e., words that cannot be clearly identified as loans, also at an early (proto-language) state. However, the uncertain etymology is marked in the legend text (appendix 3b), as well as in the more careful etymological descriptions in the database DiACL. A substantial amount of words in the data have no etymologies, and this is particular the case for non-Indo-European families. These words also receive the coding 1 and 3, in contrast to words that are borrowed. Words coded as loans (2 and 4) are evident borrowings, where a source language or a source language family/branch can be identified. Words that are calques are not coded as borrowings: the formal etymology of the lexemes is the source of the coding. This coding system, which is important to data filtering, is given for each lexeme in appendix 3b. For statistics, we have also introduced other metrics, which are of relevance to the investigation of behavior of the data. In the following chapters, we will describe how the coding has been used in visualizations and statistics (see also table 36).

6.3.3 Principles of maps: cognacy maps and loanword flowmap Cognacy maps visualize lexemes of attested languages (contemporary/historical) and display data only by concepts (e.g., bull, apple, sheep). The occurrences of lexemes are given by numbers indicating their cognacy, which is explained in the map legends. Explanations of the legends refer normally to a reconstructed proto-form with a meaning, in case such a reconstruction is possible. If a reconstruction is difficult or non-existing, the legend text gives the form of one or several languages, or, in specific cases, only the meaning. Some reconstructions or language forms are marked as uncertain, migratory, or substrate, indicating that there is a discussion in the etymological literature on the reliability of the reconstruction. In general, there is a huge discrepancy between different schools on the acceptance of etymological reconstruction. Proponents of the Leiden school, who are the authors of the Brill Etymological Dictionaries (Lubotsky 2010), an important source to our Indo-European data, frequently propose substrate origin for the type of vocabulary that we have compiled in our corpus. However, the arguments for substrate origin given in these sources are often meagre, and in many cases a proper proto-language reconstruction is definitely possible. In these cases, we have often selected to follow the precursors to the Brill dictionaries, such as (Frisk 1954, Hellquist 1948, Mayrhofer 1986, Walde 1910, Walde and Hofmann 1965) or the compilation of Indo-European nouns by (Wodtko, Irslinger, and Schneider 2008). In deciding upon the reliability, the resources by Mallory and Adams (Mallory and Adams 1997, 2006) have been important guides, besides these resources mentioned before. However, the rendering of Proto-Indo-European laryngeals as well as the morphology of reconstructions, is often adapted from the Brill dictionaries. For details, we refer to the lexical database (appendix 3b), the sources (4b), and the database. In our lexical data, in contrast to the grammatical data of the previous section of this book, there is typically more than just one lexeme for a concept in a language. Here, we have selected a policy where the main lexeme of a language representing the core meaning yields the color of maps. In this way, colours of maps represent the preservation of the core meaning of a specific etymology. The map color is given independent of whether a lexeme is inherited or loaned, but cases of inheritance versus loan are indicated by the symbols of the map (■ = core meaning,

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inherited, □ = core meaning, loan). Lexemes of extended or slightly changed meaning, or of dialectal, rare or obsolete usage, (coding 3,4) are also given on maps, but they have secondary priority and do not impact the color of maps (● = extended meaning, inherited, ○ = extended meaning, loan). The numbers in the legend, which in the maps follow immediately upon the symbol, indicate the presence of a cognate in a language, either as core meaning (1,2) or as in extended meaning (3,4). Lexemes that have changed their meaning (marking 0) are removed from the maps. However, they are given in appendix 3b and they form an important foundation for the colexification and meaning change charts (6.3.4.). For the policies motivating our coding, see 6.2.2. The data set also contains a relatively substantial number of lexemes which have not been coded for cognacy and hence lack a connection in the database. This has various reasons, one of them being lack of adequate dictionary resources (cf. appendix 4b), another being absence of reliable background research. However, this data still contains many valuable and new lexemes, among others compiled by fieldwork (appendix 4a), for future etymologists to work with. Therefore, we include these lexemes, but always with the marking (no etym.) and after the etymologized lexemes on maps. Towards the end of the lexical atlas section, we have created a loanword flow map (map 57), which is based on lexemes that are coded as loans (2,4) in our data (appendix 3b). Loans in our data include words that are reliably reconstructed as loanwords, which by definition means that the source language can be identified. Hence, loan does not include early migration words and lexemes that are supposed to be loans from an unknown substrate. In our data, the source language of loans is either an existing language, living or extinct, a proto-language state (ProtoIndo-European, Proto-Indo-Aryan), a language family (Turkic), or a sub-branch (Germanic). For the loanword flow map, we have used our assumed position of the proto-language of the family or branch as the location (see appendix 3d). From this location, we have drawn an arrow to the target language location, also marked by a focal point. It is important to remember that this map only gives us an indication of directions of contact; the map gives no exact information on areas of language contact. As an example, the position of Proto-Turkic is not at all indicative of where Turkic loans may have entered Iranian or Caucasian languages. Likewise with Indo-Iranian and Uralic. Nevertheless, the map gives important information on the zones of language contact (see further discussion under 6.13, appendix 3b).

6.3.4 Colexifying and co-cognatic meaning charts These charts, which are an extension of polysemy and colexification networks (List et al. 2018, Fellbaum 1998), are based on data from the Indo-European and Caucasian families, visualize patterns of colexification (polysemy) and meaning change in the data (François 2008, Geeraerts 2010, 23–41, 1997). Like in maps, meanings are extracted from attested languages only, indicating that reconstructed colexifications and meaning changes are not included. The reason for using only Indo-European and Caucasian data for these charts is that these families are well enough covered by cognacy and have a sufficient number of languages. The charts include several concepts, which are grouped into different charts by their mutual colexifications and meaning changes. The aim of the charts is to two-fold: first, to identify a method to organize and classify Word List concepts by their patterns of mutual colexification and meaning change, and second to organize meanings hierarchically by their frequency of mutual occurrence by colexification (synchronically) as well as their cooccurence in etymological trees (diachronically). For this purpose we use two concepts: colexifying (François 2008) and cocognatic meanings (cf. appendix 3b). Meanings are derived from the meaning field and standardized and adapted. The two concepts can be explained as follows:

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– –

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Colexifying meanings: meanings that co-occur, by polysemy, in the synchronic state of a language; Co-cognatic meanings: meanings that are diachronically connected by cognacy, sharing the same ancestor.

As we will see later on (6.4–6.13), colexifying and co-cognatic meanings of concepts coincide with their cultural functionality, following the culture-based classification of concepts that we have outlined in the introduction (chapter 2). This is highly interesting and proves the strength of our method of following a culture-based classification. In the charts, colexifying and co-cognatic meanings are displayed differently. The charts contains circular nodes of various sizes, connected by lines. The circular nodes are coloured hierarchically (by their distance to the Word list concept meaning) by the colours green > blue > purple > red. These colours and their internal hierarchy are to be interpreted as follows: – Node color – Green implies that the meaning is a Word List concept meaning, e.g., bull, grain (see table 35); – Blue implies that the meaning colexifies with at least one Word List concept meaning in at least one of the featured languages; – Purple implies that the meaning colexifies with at least one Word List concept meaning in at least one of the featured languages, which is also co-cognatic (i.e., connected by cognacy) in at least one of the featured languages; – Red implies that the meaning is co-cognatic with at least one Word List concept meaning in at least one of the featured languages; – Node size – Node size is determined by the number of connections to other nodes. Word List concepts are often the largest nodes, but not always: meanings which are not Word List concepts may be more ‘central’ in the sense that they occur more frequently in colexifications. – A connection between two nodes indicates that the meanings of both nodes occur as colexifying meaning in at least one of the featured languages. – Line color is determined by the parent node, which is decided by the following hierarchy: Core concept meaning > Colexifying meaning > Colexifying/Co-cognatic meaning > Co-cognatic meaning. – Free floating nodes or node clusters are lexical meanings that are not connected to the Word List concepts directly or indirectly in any of the featured languages. These are meanings that occur in etymologies (but are connected as co-cognatic meanings). If they are connected by a line, it implies that they co-occur by colexification somewhere in the data. The listed meanings of colexification charts were extracted from the meaning fields of etymological trees of the database, which form the basis for appendix 3b and have been described in 6.1.5. In the database, the meanings of lexemes are mainly derived from dictionaries (appendix 4b). Dictionary meanings are often very detailed, and when they are compared on a mass basis, as here, substantial amounts of meanings are redundant. For the purpose of the colexifying charts, it was necessary to make a complete revision of the meaning fields of the database (rendering the exact meaning of words in languages), which simplified and conflated redundant meanings. In the colexification charts, the absolute number of colexifying and co-cognatic meanings is not included. The size of bullets corresponds to number of connections to other bullets, which is a relative number (i.e., the absolute number of connections may vary). This has several reasons. First, the necessary simplification of meanings made it difficult to keep track of the absolute number of connections between meanings. Second, it was impossible to account for colexifying and co-cognatic meanings in a systematic manner that would be necessary for counting meaning

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occurrences. We admit that this is a weakness of the charts, since it would have been of high value to know, in absolute numbers, which type of meaning change and colexifications are more common than others. However, the charts give valuable information on semantic connections within the data, synchronically and diachronically, and they turn out to be of high value to the interpretation and evaluation of the culture vocabularies (6.4–6.13). The graphs were produced by the clustering software Gephi (Bastian, Heymann, and Jacomy 2009). In evaluating the charts, it is important to focus on hubs at the center of the charts, e.g., meanings that occur frequently together with our Word List concepts, rather than meanings that occur occasionally in charts. The marginalized connections are based on stray meaning changes in the data and are thus of lower value from a general perspective. Colexifying and co-cognatic meaning charts present a huge variation of meaning connections, typical for semantic change, such as generalization, specialization, metonymy, metaphor, synonymy, synecdoche, hyperbole, amelioration, and pejoration. In particular, an abundance of meaning connections represents various specializations of our lexical concepts, such as various species of animals or plants. However, if the selected concept has a more specialized, cultural meaning (e.g., cultivated field), the connected core meaning (e.g., field) often has a larger prominence, i.e., a more central position in graphs. For our purpose, the metaphor and metonomy changes are of great importance, since they give useful information about the relation of cultural concepts to each other, as well as their cultural function and status. They are also helpful for classifying concepts culturally: the presence of shared colexifying and co-cognatic meanings can be used to classify concepts. As we will see in the charts, the semantic content of the meaning is of higher relevance than the word class. Most concepts in our data are nouns; only a few are verbs, none are adjectives. However, in colexifying and co-cognatic meaning charts, word class is secondary, and verbs and nouns (together with adjectives) typically cluster by semantic and cultural domain. In addition, charts inform us about concepts that we should have included. Almost every chart reveals missing concepts, which turn out in the center of networks, falling out of the colexifications and meaning changes of other concepts (cf. fig. 30). Finally, it is important to note that the networks of charts give no indication of directionality of change. The basis for graphs is a list of meanings that co-occur in etymological trees with a connection to concepts. The charts will be mentioned several times in our chapter on lexicon and form an important foundation for evaluation of data according to a cultural model.

6.3.5 Statistics: borrowability, semantic variability/instability, colexification, cognacy productivity, and gender We perform a number of statistical tests on our data, based on the coding system described in 6.3.2. Based on the coding, there are several parameters for which we believe that the data has enough coverage and has been coded in a manner that we can perform statistical tests. For other parts, we have – for various reasons – preferred not to perform statistical tests. This will be further described below. First, we are interested in the concepts’ borrowability. Borrowability measures the degree to which a concept lexeme is borrowed, independent of whether the lexeme represents the core concept or whether it has extended its meaning (codings 1–4) (note that this method is different from, e.g., (Haspelmath and Tadmor 2009). Therefore we measure borrowability as the percentage of borrowed lexemes (codings 2,4) in relation to the total number of lexemes per lexical concept (codings 1–4). The absolute numbers and percentages are given in appendix 3c. Further, we are interested in the concepts’ semantic instability and variability. We measure this in two way, first, semantic instability and variability we we measure by the codings 3–4 (contrasted to 1–2), which includes colexified meanings with the original meaning preserved, slight deviations in meaning, and dialectal and obsolete forms. Hence, we measure semantic instability and variability by the amount of 3–4 in relation to the total number of lexemes per

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Tab. 36: Overview of semantic coding types of lexemes and their inclusion in visualizations (maps, graphs). Coding Type (see 6.3.2)

Example

Cognacy maps

Colexification charts

Statistics

1

Core meaning/ Inherited

apple

y

y

y

2

Core meaning/ Loaned

apple

y

y

y

3

Extended meaning/ Inherited

fruit; apple

y (secondary priority)

y

y

4

Extended meaning/ Loaned

fruit; apple

y (secondary priority)

y

y

0

Changed meaning/ Inherited

apple tree

n

y

n

0

Changed meaning/ Loaned

apple tree

n

y

n

lexical concept. Absolute numbers and percentages are given in appendix 3c. Visualizations are given under respective chapter and in 6.13. Further, we measure the total amount of colexifying forms (lexemes with more than one meaning) in all words marked by 1, 2, 3, or 4 (appendix 3c). In our data, we also have a substantial amount of lexemes which are connected by cognacy but which have changed their meaning by metaphor, metonymy or other types of change. These are coded as 0 and excluded from the lexical maps and the statistics (see table 36). We decided to exclude also these lexemes from statistical tests on semantic instability. This has several reasons; most importantly the status of the data. For Indo-European, a systematic study of semantic change would be possible, for the other families, the situation would be more complicated. Further, we also have the method of compiling data: for Indo-European, a compilation of data from etymological dictionaries is possible, where lexemes can be traced and compiled systematically from the reconstructed proto-roots up to the attested languages. For the other families, this type of compilation is not possible yet. In addition, it is difficult to decide when to include or exclude an etymologically related form. Lexemes may or may not have various types of morphological derivations, and we have applied a set of rules for including or excluding etymologically related lexemes in trees (see 6.1.2). However, we do not consider these rules to be applied consistently enough on the data to perform statistics on the lexemes with semantic change, which are marked by 0 (see appendix 3b). On the other hand, changed lexemes are included in the colexification and meaning change charts (6.3.4), where a counting of absolute number of occurrences is not applied (see 6.3.4). The principle to include semantic variation by specialization/generalization and colexification but not change by metaphor/metonymy in statistical tests may give rise to interesting results. For instance, some Word List concepts may have a substantial amount of connotations and connections in meaning change graphs, but still a low score on semantic instability and variability, such as the concept wolf (see 6.4.3). This indicates a tendency for the lexemes of a concept to be involved in meaning change, but without intermediary colexification; e.g., if a lexeme changes from wolf to criminal or vagabond, then it does not keep the original meaning by colexification. A third metric of interest to us is colexification rate, which we measure by counting the frequency of colexifying meanings in relation to the total amount of meanings of lexemes coded as 1–4 (excluding changed lexemes, 0). As mentioned earlier, colexified meanings in the meaning field are distinguished by semi-colon, whereas synonymous meanings are marked by comma. As an example we may take Modern Armenian hut meaning field [grain, seed; piece, cut]. The meanings [grain, seed] and [piece, cut] are synonymous; whereas [grain, seed] and [piece, cut] are colexifications.

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Further, we are also interested in cognacy productivity, which we measure by the number of unique cognacy values (i.e., Top node numbers, see appendix 3b), in relation to the total number of lexemes for a concept coded as 1–4 (excluding changed lexemes, 0). In principle, if a concept frequently undergoes lexical substitution, the total number of unique cognacy values per concept is higher. A more stable concept has fewer cognacy values. The four metrics, borrowability, semantic instability/variability, colexification, and cognacy productivity, which are all in percentages, may be accumulated to retrieve an index of a concept’s general behavior in terms of inherent propensity to change. In particular, the differences between borrowability, semantic instability/variability, colexification, and the relation to lexical substitution and lexical change rates (see 6.3.6) is highly interesting and have far-reaching cultural connotations (see further 6.13). All lexical statistics is given in appendix 3c. In sections 6.4–6.14, there are scatterplots with individual concepts by their classifications (table 35). These scatterplots display the relationship between Instability (on the y-axis), Loan (on the x-axis) and Cognacy (as the circle size) for the individual concepts in the respective class. The combined scatterplot of all classes (fig. 52) displays the relationship between Instability (on the y-axis), Loan (on the x-axis) and Cognacy (as the circle size) for the major classes. The boxplots (figs. 53–56) indicate the borrowability, instability, colexification and cognacy variables per major class. Black vertical lines are median, hinges correspond to the first and third quartiles, black dots are outliers. The basic statistics for the appendix 3c is performed by Excel Pivot tables, the scatterplots and boxplots ware computed in R (https://www.r-project.org/). Plots are visualized by the ggplot2 package (Wickham 2009).

6.3.6 Statistics: gender Besides these four metrics (borrowability, instability, colexification, cognacy) discussed in previous chapter, which fundamentally aim to study lexical change and substitution patterns of our data, there is another metric, which is of relevance to a cultural model, and which bridges the lexical section to the grammar section, namely gender. A substantial part of our data is from the Indo-European family, within which the dominant pattern of nominal classification is gender (5.4.2). Many Indo-European languages have preserved a three-gender system of masculine, feminine, and neuter, others have merged to masculine – feminine or common gender – neuter (see map 7). As we have seen in 5.7.2, the evolutionary model reconstructs a three-gender system (masculine, feminine, neuter) for Proto-Indo-European, and this system has also been preserved in many languages. Gender typologically ranges under the umbrella of classifyers, e.g., grammatical categories that classify objects and entities of the surrounding environment. In languages with a gender system, a classification that fundamentally targets sexus is projected onto the entire system of nouns. What is of interest to use here, are the tendencies of gender assignment in relation to our concepts and classes, which is related to the discussions on semantics of gender assignment (e.g., Corbett 1991, 7–32, Matasović 2004, Mithun 2013). The percentages of the genders common gender, feminine, masculine, and neuter are given in table 37. These patterns are highly relevant and very interesting in contrast to the other metrics, borrowability, variability/instability, and cognacy. We will have reasons to return to the gender in discussions later on.

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Tab. 37: Percentages of the genders common gender (c), feminine (f), masculine (m), and neuter (n) of the 6727 lexemes in the data that have a secured assigned simple gender (0 excluded, vacillating gender and alternans excluded, Indo-European languages only). Classes (in bold) give an average of the gender rates of concepts of the class. For an overview of gender systems in our languages, see map 7. CLASSES and concepts

 c

 f

 m

n

CATTLE bull calf cattle (coll.) cow CROPS barley flax grain (generic) oats rye wheat DOMESTIC ANIMALS cat dog DOMESTIC INSECTS bee DRAFT ANIMALS donkey horse ox DRINK AND DRUGS mead wine GAME ANIMALS bison deer hare rabbit wild boar IMPLEMENTS knife saw scythe sickle spade MATERIALS fur grease leather meat stone wood METALS copper gold iron silver PIG RAISING pig piglet POULTRY chicken duck hen rooster

4,26 % 5,88 % 4,76 % 0,00 % 6,38 % 4,16 % 5,26 % 2,82 % 2,02 % 6,67 % 6,00 % 4,17 % 5,00 % 4,92 % 5,05 % 1,56 % 1,56 % 3,27 % 1,15 % 3,66 % 5,45 % 3,96 % 3,64 % 4,35 % 5,59 % 11,90 % 7,54 % 4,41 % 4,00 % 0,94 % 5,78 % 5,26 % 9,09 % 3,03 % 4,69 % 6,54 % 2,79 % 5,26 % 1,95 % 2,88 % 0,00 % 4,23 % 0,99 % 0,40 % 1,08 % 0,00 % 0,00 % 0,00 % 7,10 % 6,85 % 11,11 % 4,11 % 5,19 % 4,48 % 3,45 % 3,33 %

22,13 % 5,88 % 9,52 % 9,84 % 78,72 % 22,49 % 26,32 % 15,49 % 16,16 % 31,67 % 30,00 % 22,22 % 28,13 % 47,54 % 16,16 % 68,75 % 68,75 % 15,69 % 13,79 % 20,73 % 3,64 % 4,95 % 7,27 % 2,17 % 18,92 % 0,00 % 27,64 % 19,12 % 16,00 % 11,32 % 50,75 % 21,05 % 78,79 % 65,15 % 53,13 % 49,53 % 33,48 % 38,60 % 24,68 % 47,12 % 27,27 % 41,55 % 19,80 % 5,93 % 11,83 % 1,92 % 5,88 % 0,00 % 31,61 % 33,56 % 0,00 % 41,44 % 35,06 % 73,13 % 65,52 % 7,78 %

53,19 % 87,06 % 66,67 % 34,43 % 4,26 % 46,21 % 38,60 % 50,70 % 30,30 % 58,33 % 54,00 % 54,17 % 65,00 % 47,54 % 75,76 % 21,88 % 21,88 % 66,34 % 73,56 % 54,27 % 90,91 % 61,39 % 65,45 % 56,52 % 64,52 % 88,10 % 54,77 % 76,47 % 70,00 % 63,21 % 34,92 % 52,63 % 10,61 % 27,27 % 35,94 % 38,32 % 30,69 % 30,70 % 38,96 % 12,50 % 6,06 % 52,11 % 22,77 % 42,29 % 48,39 % 38,46 % 37,25 % 40,35 % 36,77 % 34,93 % 66,67 % 46,92 % 40,26 % 17,91 % 24,14 % 88,89 %

20,43 % 1,18 % 19,05 % 55,74 % 10,64 % 27,14 % 29,82 % 30,99 % 51,52 % 3,33 % 10,00 % 19,44 % 1,88 % 0,00 % 3,03 % 7,81 % 7,81 % 14,71 % 11,49 % 21,34 % 0,00 % 29,70 % 23,64 % 36,96 % 10,97 % 0,00 % 10,05 % 0,00 % 10,00 % 24,53 % 8,54 % 21,05 % 1,52 % 4,55 % 6,25 % 5,61 % 33,04 % 25,44 % 34,42 % 37,50 % 66,67 % 2,11 % 56,44 % 51,38 % 38,71 % 59,62 % 56,86 % 59,65 % 24,52 % 24,66 % 22,22 % 7,53 % 19,48 % 4,48 % 6,90 % 0,00 %

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Tab. 7 (continued) CLASSES and concepts

 c

 f

 m

 n

PREDATOR ANIMALS bear fox jackal leopard lion lynx snake wolf PREDATOR BIRDS eagle owl raven PRODUCTS honey hops milk salt wax (bees) wool SEASONS autumn harvest spring summer winter SMALL CATTLE goat kid lamb ram sheep (coll.) TILLAGE cultivated field furrow plow (n) TREES beech birch elm oak WEAPONS arrow axe bow spear sword VEGETABLES & FRUIT apple grape turnip VEHICLES axle hub wagon wheel yoke

5,60 % 4,69 % 5,13 % 11,11 % 8,75 % 1,79 % 6,90 % 5,24 % 5,00 % 5,20 % 5,88 % 6,41 % 3,85 % 3,34 % 6,12 % 2,56 % 3,28 % 0,00 % 2,13 % 5,26 % 5,23 % 4,55 % 3,23 % 4,11 % 5,97 % 7,25 % 3,31 % 5,50 % 0,00 % 0,00 % 5,75 % 2,02 % 5,00 % 3,81 % 9,09 % 3,75 % 6,00 % 9,09 % 3,85 % 0,00 % 0,00 % 4,87 % 3,23 % 7,14 % 7,27 % 4,46 % 0,00 % 2,88 % 1,54 % 2,20 % 5,77 % 3,66 % 4,04 % 3,92 % 8,06 % 2,50 % 0,00 %

31,20 % 18,75 % 47,44 % 5,56 % 13,75 % 10,71 % 34,48 % 50,26 % 15,00 % 33,20 % 30,88 % 43,59 % 26,92 % 34,65 % 12,24 % 10,26 % 34,43 % 28,07 % 34,04 % 67,11 % 31,70 % 25,76 % 58,06 % 41,10 % 19,40 % 27,54 % 29,26 % 44,04 % 5,71 % 3,17 % 8,05 % 56,57 % 37,50 % 33,33 % 67,27 % 22,50 % 64,00 % 68,18 % 61,54 % 100,00 % 0,00 % 46,68 % 67,74 % 69,48 % 7,27 % 36,61 % 24,64 % 47,60 % 27,69 % 51,65 % 65,38 % 31,83 % 50,51 % 45,10 % 9,68 % 27,50 % 19,05 %

60,96 % 76,56 % 46,15 % 77,78 % 73,75 % 78,57 % 55,17 % 43,46 % 80,00 % 60,00 % 61,76 % 47,44 % 68,27 % 39,51 % 53,06 % 84,62 % 32,79 % 33,33 % 34,04 % 21,05 % 46,73 % 45,45 % 38,71 % 31,51 % 52,24 % 62,32 % 48,85 % 48,62 % 40,00 % 52,38 % 83,91 % 19,19 % 42,92 % 41,90 % 23,64 % 57,50 % 28,00 % 18,18 % 34,62 % 0,00 % 100,00 % 34,73 % 27,42 % 18,83 % 78,18 % 33,04 % 44,93 % 34,13 % 38,46 % 37,36 % 23,08 % 38,87 % 36,36 % 37,25 % 75,81 % 26,25 % 23,81 %

2,24 % 0,00 % 1,28 % 5,56 % 3,75 % 8,93 % 3,45 % 1,05 % 0,00 % 1,60 % 1,47 % 2,56 % 0,96 % 22,49 % 28,57 % 2,56 % 29,51 % 38,60 % 29,79 % 6,58 % 16,34 % 24,24 % 0,00 % 23,29 % 22,39 % 2,90 % 18,58 % 1,83 % 54,29 % 44,44 % 2,30 % 22,22 % 14,58 % 20,95 % 0,00 % 16,25 % 2,00 % 4,55 % 0,00 % 0,00 % 0,00 % 13,72 % 1,61 % 4,55 % 7,27 % 25,89 % 30,43 % 15,38 % 32,31 % 8,79 % 5,77 % 25,63 % 9,09 % 13,73 % 6,45 % 43,75 % 57,14 %

4,25 %

31,78 %

46,45 %

17,51 %

TOTAL

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201

6.3.7 Evolutionary reconstruction of meaning gain and loss In analogy with the evolutionary reconstruction model of grammar described in chapter 5.7.2, we have also attempted to construct a model for reconstructing meaning gain and loss. The work is still in progress but may be mentioned here alongside with our evolutionary reconstruction of grammar. We adapt a simple model of meaning change, which assumes that an etymon (here, all lexemes of an etymological tree, independent of coding 0–4) can gain or lose a given meaning with a certain probability at some time interval (see Maslova 2000 for an application of this model to grammatical change). A practical choice of time interval is that between a proto-language and its daughter (as per known language subgrouping relations), though this choice could be improved on if actual time depths were known confidently. Since an etymon can, in principle, colexify any number of meanings simultaneously we choose to model the gain/loss of each meaning independently. Considering a meaning M, the model requires two probabilities: that of gaining the meaning M when absent, and that of losing M when present. The meaning changes collected in the lexical dataset allow estimating these probabilities. The proportion of meaning changes toward M is a direct estimate of the probability of gaining it when absent. In the lexical dataset, the original meaning in a change is not systematically recorded, but the probability that an unknown node had the meaning M for the etymon can be guessed from checking the proportion of attested languages with M. With that assumption, the probability of losing M is reflected in the number of changes to some other meaning than M where we can expect the original to have been M, relative to the number of retentions of the meaning M. Once the gain/loss probabilities are known, the probability of successive internal nodes having a certain meaning or not can be efficiently calculated from the leaf node meanings using the peeling algorithm (Felsenstein 2004, 253–254). We test this for all of our 1,165 etymological trees in the dataset. The result is, as with grammar data, a probability (0–1) of the presence of meanings in an etymological tree at ancestral nodes inside the tree. Even though our model is still under development, we clearly see a tendency. Some of the proto-language reconstructions give a high probability of one specific meaning over the other meanings, whereas in other cases, most meanings are equally probable (around 0.5). We exemplify this on an often discussed object of Indo-European, the word for ‘wheel’ (Heggarty 2014), with the two roots PIE *kʷel-o- and PIE *Hróth₂o- (table 38) (Carling, Hammarström, Cronhamn, Farren, et al. Forthcoming, Carling, Hammarström, Cronhamn, Svensson, et al. Forthcoming).

6.3.8 Interim summary: Lexicon The previous chapters have described the coding system used in the lexical data set, which forms the basis for the map visualizations and statistics. The coding system represents generalizations about lexemes, which are based on shared cognacy as well as a meaning correspondence. In our data set, there is a large amount of variation in the extension and type of lexical cognacy, but the variation is not endless, and it reflects the reality of a typological variation and diversity over the area. Our lexical data embraces the main domains of basic and culture vocabulary, focusing on semantic domains of importance to subsistence (see 6.2.2). These domains have been selected due to their presumed relevance to linguistic and cultural change. We have, as elsewhere in this volume, selected to include data from ancient languages as far as possible and therefore the applications, results, maps, graphs, and statistics of chapter 6, as in chapter 5, reflect an attested change spanning over 3,700 years, and a reconstructed change reaching several millennia beyond that. Besides lexical cognacy, i.e., an ultimate common origin of lexemes far back in time, paths of semantic change are also of high interest to an approach such as ours. The way in which we have coded etymologies allows for a systematic tracing of

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Tab. 38: Probabililies at the ancestral node of the proto-langue (Proto-Indo-European) for the different meanings of the etymological trees of PIE *kʷel-o- ‘wheel, circle’ (79981) and PIE *Hróth₂o- ‘wheel, circle’ (80116) by means of evolutionary reconstruction, calculating gain/loss probabilities over a reference tree (from Glottolog), using a peeling algorithm (Felsenstein 2004). PIE *kʷel-o- ‘wheel, circle’ (79981)

PIE *Hróth₂o- ‘wheel, circle’ (80116)

Meaning wheel to be take place disc of the sundial to become pole axis world axis circular object ring vault of heaven chariot cart neck wagon football ball throat circle

Meaning wheel chariot wagon round cylindrical object to run to roll ring sun (pl.) cart easy role to rotate cart rotate wheel-rim heaven flow aura

Probability 0.93 0.56 0.56 0.56 0.56 0.56 0.56 0.56 0.56 0.56 0.56 0.51 0.51 0.50 0.50 0.50 0.50 0.50 0.40

Probability 0.99 0.86 0.86 0.53 0.52 0.51 0.51 0.50 0.50 0.50 0.50 0.50 0.50 0.50 0.50 0.50 0.50 0.50 0.50

semantic change in lexical meanings, yielding important and interesting information about the cultural connotations and daily use of concepts and artifacts. Basic vocabulary are popular in statistical approaches to language evolution and change ever since the emergence of the lexicostatistical approach in the 1950s (Swadesh 1952, 1955). A number of papers, pro and against, have been published since then (Hoijer 1956, Blust 2000). We may refute the idea of using basic vocabulary for exact chronological dating, but never the less, basic vocabularies, if loans are removed and we use a character-based model of data coding, may produce accurate trees of splits and divergence of language families (fig. 3). The idea of basic vocabularies were already from the beginning to produce a list of concepts that was “culture-free” (Swadesh 1955), i.e., independent on cultural artifacts or habits, and “universal”, in the sense that lexical meanings were common to all languages. However, basic vocabulary data are useful in statistical and evolutionary studies, where a basic, common metric is necessary for testing gains and losses of other types of data against a tree that mirrors divergence as close as possible. Even today, basic vocabulary, represented either by a Swadesh (Swadesh 1955) or a Leipzig-Jakarta (Tadmor and Haspelmath 2010) list serve as the main basis for testing rates of change of other data types, such as typology (Cathcart et al. 2018, Greenhill et al. 2017). Overall, the causalities of lexical change, basic vocabulary or else, are not known. Language conctact and borrowing may lead to convergent patterns, but there are also indications that language contact may lead to increased divergence (Ellison and Miceli 2017). The purpose of this section is to investigate cultural causalities for change patterns in lexical data. In the following chapters (6.4–6.12), we will describe the domains, classes and investigated concepts of the lexical data. As outlined in chapter 2, we believe that a cultural model can explain lexical change and therefore, we contextualize our selected concepts words by their cultural history and prehistory, from various perspectives, before discussing the results. The contextualizations give an overview of cultural (archaeological, ethnographic, historical, mythological) history and prehistory of the semantic classes or domains of languages, branches and families of the area. Here, the purpose is to aim at understanding or even predicting the results of the various patterns emerging from the results, which are summarized in chapter 6.13.

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6.4 Hunting and trapping 6.4.1 Introduction Over the Eurasian continent, agriculture gradually became the dominant subsistence system between 10,000–5,000 BP, spreading from a core area of Anatolia and West Asia and to the north, east, west, and south, leading to dramatic changes in population structure. However, the activity of hunting continued to play a role among Neolithic farmers. From early Neolithic excavation sites, such as Ҫatalhöyök, bones of wild species of animals, such as deer, wild horse, and wild donkey, are found besides the recently domesticated animals, such as sheep, cattle, and goat (Martin 2000). Hunting continued to be a complement to agriculture, adapting to the climate (Carruthers 2003). The activity of hunting itself had similarities over the entire area, but the hunting game differed with respect to the environment, depending on climate zones and natural habitat of game and predator animals. Several main types are found over the entire area, including large and small game animals, such as bovids (Bovidae), deer (Cervidae), pig (Suidae), hare (Leporidae), and carnivoran predators, such as bear (Ursidae), cat (Felidae), mustelid (Mustelidae), and various types of canid (Canidae) species. The geographic extension of various species often overlaps, each filling their role in the ecological system and accordingly interfering with the cultural system of the agriculturalist and pastoralist societies. Throughout history, activities of hunting and trapping (along with fishing, which is not dealt with here) continued to play a role as a complement to agriculture and pastoralism, in particular during periods of agricultural decline or crop failure. Hunting was of two types: hunting for game and protective hunting. The latter was of particular importance, both to farmers and pastoralists, serving the purpose of protecting the domestic cattle from predators. Among most ancient IndoEuropean peoples, the activity of hunting as well as the hunter himself had an important role in society (Gamkrelidze, Ivanov, and Winter 1995, 601–603, Schrader 1923, 519–525). In many areas, hunting also remained important as a valued and prestigious sport. The activities of hunting in ancient and historical times were performed in manners that have their roots in a prehistoric system, involving hounding and battue (i.e., the beating or driving of a game from cover toward a stationary hunter), assisted by dogs (Guagnin, Perri, and Petraglia 2017), as well as mass hunting and trapping (Bar-Oz et al. 2011). In outskirts of the agricultural/pastoralist area, such as northern parts of Scandinavia, where the environmental preconditions for agriculture and pastoralism were scarce and hunting long remained unregulated, the ancient type of hunting survived into the 18th and 19th centuries (Andersson and Granlund 1962, 533 ff.). This hunting involved hounding and battue, which required an organization of hunting teams of the villagers, upholding of a system of seasonal adaptation, which controlled the reproduction of game animals. As far as we know from ancient Greco-Roman sources, hunting in classical antiquity was not regulated by land owning, but the landowners were often in possession of slaves who performed hunting as a profession (Pauly and Wissowa 1914, 563). Even though the cultivated land was owned, animals of the forests, fields and waters were not owned and free for hunting. Hunting has several cultural connotations. One of them is the high value attributed to the fur of precious animals (6.8.1), in particular the fur of predator animals, which remained an important and valued trade commodity throughout antiquity (Schrader 1929, 156–159). Another aspect is the weaponry and other technology used for hunting, such as net traps, wraps, bows, arrows, and spears (6.10.1). A third, but nonetheless important aspect, is the domestication of the dog (6.5.2) and predator birds, such as the falcon and eagle, for tracking in hunting. The hunted animals were of two types, game animals (6.4.2) and predators (6.4.3). This reflected the main types of hunting, game and protective hunting. Predators as well as game animals such as deer had a specific position among the hunted animals; surrounded by taboos and euphemisms, they were highly valued as hunting prey. More than anything, Greco-Roman mythology mirrors the societal role of hunting as an act of defense against a raging, threatening nature. It is represented by the goddess of the hunt,

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Artemis, who passes on knowledge of hunting and handling of hunting dogs via the centaur Cheiron to the ancient heroes. Hunting was an important activity of festivals and festivities, and so was the sacrifice to the gods of a portion of the killed animals: the game was apprehended as a gift from the gods (Pauly and Wissowa 1914, 558–603). The attributes of hunting are also reflected in the mythological depictions of the gods of hunting, such as Artemis and Perseus, who occur in the company of their hounds, using bows, arrows, and spears, hunting hares, deers, wild donkeys and goats. The tale of Orion, both a constellation and a mythic hero, embodies the valued role of the hunter in ancient society. Orion was a giant, a hunter, and a hero, but attracted the envy of the gods and was eventually killed by the hunting goddess Artemis. The constellation Orion hunts a bear, Ursa Major, and is accompanied by hounds and a club (Roscher 1897–1902, 1018–1048). In Nordic mythology, hunting and the hunter is less prevalent than in Greco-Roman mythology. The role of the hunter is taken by the main god Odin, whose nightly hunting activities with horses and hounds in the sky became important in Nordic folklore, the origins of which are somewhat obscure (Andersson and Granlund 1967, 503–510). Under the heading of hunting and trapping, we have compiled lexical meanings for the prey of the two hunting types, game and protective hunting, dealt with under Game animals (6.4.2), Predator animals (6.4.3), and Predator birds (6.4.4), for which there is a significant amount of reconstructable, wide-spread and stable roots but also concepts which demonstrate a high degree of continuous lexical substitution. For the implements used for hunting, such as bow, arrow, spear, we refer to Weapons and warfare (6.10).

6.4.2 Game animals The main game animals were of the bovid (Bovidae), cervid (Cervidae), pig (Suidae), equid (Equidae), hare (Leporidae), and duck/goose (Anatidae) families. Several of them had a domesticated counterpart, e.g., bison (domesticated cattle), wild goat (domesticated goat), wild boar (domesticated pig), wild goose (domesticated goose), and wild duck (domesticated duck). These animals have different domestication histories (6.5), but the hunting in several occasions, such as for the cattle, sheep, and goat, played an important role in the animals’ domestication process (Larson and Fuller 2014). Other game animals in prehistoric and ancient times existed mainly in the wild, of which the most important were the deer and the hare. The deer, an important hunting prey already during the Mesolithic and Neolithic periods, incorporates a number of species of cervids, with different extensions over the area, most important being the red deer (Cervus elaphus) with a historical spread in Europe and present in Western Asia to present-day Bhutan, the roedeer (Capreolus capreolus) with a spread that includes Europe until present-day Southern Iran, and the fallow deer (Dama dama), whose natural distribution included the Mediterranean and was first introduced in Northern Europe during the Middle Ages (Mallory and Adams 1997, 155, Andersson and Granlund 1961, 612–613). The hare is found over the entire area including the Indian subcontinent, mainly with the species Lepus europeus and Lepus nigricollis (on the Indian subcontinent). The most important hunted wild bovid, found over all of the area, was the huge aurochs (Bos primigenius), the ancestor of all domestic bovids. Besides, we have the European bison (Bison bonasus), which was found in all parts of our targeted area except for the Indian subcontinent (Mallory and Adams 1997, 136–137). The natural habitat of the wild boar (Sus scrofa), ancestor of the domesticated pig, was extended over the entire area including the Indian subcontinent, but excluding Central Asia and northern parts of Northern Europe. The wild goat had a more restricted extension, historically from Anatolia over Central Asia and Caucasus to Southern Afghanistan. Game animals were hunted basically for their meat, making the large game animals (deer, bison) particularly valued as prey. The hunting procedure, as it is described from Greco-Roman sources (Pauly and Wissowa 1914, 583–595), differed between the targeted animals, and the difficulty involved in hunting had an influence on the societal value of the hunting type. It is likely

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that these hunting types, as they are described here, differ little from earlier to later methods. Hunting of hares was performed by dogs, using nets and traps as a complement. Deer were chased by hunters, typically on horseback, accompanied by dogs and armed by spear and bow. Using traps as an aid had a low societal value. The hunting of the wild boar was particularly dangerous and was regarded as prestigious and heroic. This hunting was done by tracking, using dogs (wild boars have a tendency to hide in the forests in order to escape), and the final capturing and killing of the wounded animal, the most risky part due to the sharp tusks of the animal, was done with or without a net, normally using dogs and a spear. The hunting of the wild goat involved a different procedure: the lurking, lone hunter waited for his prey and killed it from a distance with one well targeted arrow. The bison or aurochs was chased by hunters on horseback, using spears. It is described that the animals were often hunted into pitfalls, in order to use the animals for bull baiting or domestication. Among the game animals, in particular the deer and its primary attribute, the antlers, plays a central role in mythologies. This is prominent in Central Asian myth and ritual, but stretches all the way into Europe and continues from ancient times into the Middle Ages (Laurant and Zarcone 2017). Among Caucasians, the deer was apprehended as a highly sacred animal, whose antlers were associated with the tree of life, a central concept in Caucasian mythology (Ochiauri and Surguladze 1980, Khutsishvili 2010). For Indo-European wild animals in general (see also 6.4.3, 6.4.4), we can reconstruct fauna including the game animals including hare, bison, boar (wild/domestic), elk, deer, goat (wild/ domestic), including specializations (e.g., by sex and age) (Fortson 2010, 44, Mallory and Adams 2006, 135). Here we have selected to look at the core concepts wild boar, bison, hare/rabbit, and deer. For bison and for wild boar, there are many co-occurrences with the domestic counterparts, both in etymology as well as in semantic change (both in Indo-European as well as in Caucasian). Therefore we have decided to treat them together, i.e., with Bovine cattle (6.5.5), and Pig raising (6.5.4), in colexification and meaning change charts. Beginning with hare/rabbit (appendix 3b), we notice that there is a substantial amount of replacement and taboo words, referring to, e.g., ‘the one with long ears’ (e.g., Wel ysgyfarnog ‘hare’ and other Brythonic ‘ear’-words), ‘the grey one’ (PIE *ḱh₁-s-, *ḱeh₁-s- ‘grey’), ‘the one with a tail or a penis’ (PIE *pesḗn- ‘possessed of a penis or tail’), ‘the urged one’ (BSl *zuojekas ‘hare’ < PIE *ǵhey- ‘spur, incite’), or ‘the donkey-eared’ (MPers xar-gōš ‘hare’, lit. ‘donkey-eared’). The Caucasian data unveils a different pattern (appendix 3b): hare/rabbit etymologies lead to cognates with the meaning mole or frog, hence targeting a small animal in general. The data indicates that the hare was surrounded by taboo and superstition among Indo-Europeans, a pattern that is less clear in the Caucasian data (Kartvelians or Dagestanians). The terms for deer (appendix 3b) in Indo-European also display a very high rate of instability (fig. 13) and an extreme variety in semantic change (fig. 12), indicating a substantial amount of superstition and taboo surrounding this animal (Gamkrelidze, Ivanov, and Winter 1995, 437– 438, Laurant and Zarcone 2017, 91 ff.). On the other hand, the colexification rates as well as the borrowability rates are low for this animal. Caucasian data for deer has not been collected. Traces lead to Indo-European words with meaning ‘deer’, e.g., PIE *yorḱ- ‘a kind of roebuck’, which typically refers to the antlers (PIE *ḱer(h₂)-uo-/-ueh₂- ‘horned animal; deer, ox’, PIE *bhrendh- (?) ‘horned animal, elk, deer’, derivations from PIE *ḱem- ‘to truncate (horns)’), but also to other hunted animals (PIE *kapro- ‘buck, he-goat’, PIE *porḱo- ‘young pig, piglet’), the forest (PIE *widhu- ‘wood’), the fur (PIE *dhrono- ‘speckled, variegated’), or the activity of hunting (PIE *(H)uēnh₁-, *(H)unh₁- ‘hunt, desire’). Colexification and meaning changes of game animals follow two patterns. For a game animal with a domesticated counterpart, e.g., bison/bovine and wild boar/pig (wild goat is not a concept in our data), meanings cluster with their domesticated counterparts (fig. 23). However, these animals have some interesting connotations, where there is a difference between the wild and the domesticated variants. (Wild) boar is connected to meanings with positive connota-

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Figure 12: Colexification and meaning change of the concept deer.

tions, such as ruler, powerful, manly, hero, husband, chieftain, whereas (domestic) pig is connected to meanings with negative connotations, such as fat/ greedy/ filthy/ immoral person. Second, there are connections between game animals, independent of species. For instance, besides other pig words, boar and pig are connected to bull. Bison is interesting: apparently, bison words have no specific semantic value by themselves; rather they sort naturally under the huge cattle complex (fig. 23), which is highly complex, but will be dealt with elsewhere (6.5.5). The game animal concepts hare and rabbit have interesting connotations (appendix 3b), including brown and grey, but they do not link over to the other game animals: all colexifications and meaning changes stay within the leporid species (appendix 3b). A different scenario is found with the concept deer (fig. 12), which itself builds a huge network of highly interesting connotations, including other cervids, such as elk, but also cow and ox. A large group of meanings involve connotations that imply danger, such as beast, wild/dangerous animal, monster, brutal person, or snake, putting deer in a cultural category which is half-way to the predator animals (6.4.2), for which there are plenty of connotations implying threat and danger. Compared to concepts such as wolf, the relative absence of human metaphors (negative or positive) is worth noticing, though (see 6.4.3). The frequent replacement and semantic instability of game animals is evident from the statistical analysis of game concepts (fig. 13). The concepts rabbit and bison have high borrowability rates and low instability rates, whereas deer and wild boar are opposed; they have high instability rates and low borrowability rates. All are relatively rich in cognacy.

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Figure 13: Borrowability (x), semantic instability (y) and cognacy (node size) for GAME ANIMALS.

6.4.3 Predator animals Under the heading “predators” we target animals that we assume to have cultural connotations mainly due to their impact on settlements, both as a direct threat to humans and livestock, as well as an indirect threat to subsistence as competitors of the game. Predators involve both mammals and birds, and both carnivores hunting for live meat and scavengers. However, colexifications and meaning changes indicate a separation of mammals and birds, which have different connotations and do not overlap. Our targeted area spans over several climate zones and embraces a greater diversity in habitats of predators than game species. Predator animals in our classification include various carnivore animals (Cooke 2008, 122 ff.), embracing predators from the canid family (Canidae), including wolf, fox, and jackal, the bear family (Ursidae), including (brown and black) bear, and felid family (Felidae), including tiger, lion, lynx, leopard, and (wild) cat. The natural habitats of these animals are distributed over different zones (Cooke 2008, 62 ff.), of which most overlap in the Mediterranean area. The tiger, another important predator, existed already in prehistory solely on the Indian subcontinent and is therefore not in our list. The prehistorical and historical distribution of the lion (Panthera leo) is more uncertain. It is obvious that activities during the Greco-Roman period, such as animal baiting and gladiatorial games, made the lion extinct throughout the Mediterranean. On the one hand, we have depictions of lions as well as preserved artifacts from all over the Mediterranean area, but it remains uncertain to what extent they represent an occurrence of the lion in the environment (Mallory and Adams 1997, 356). Lions in art also occurred frequently (but mostly later, in the post-classical period) in Northern Europe, where lions never had a natural habitat (Andersson and Granlund 1966, 165– 185). The cave lion (Felix leo spelaea), an important predator during the Pleistocene, was already extinct in prehistoric times. It is likely that the cave lion was known after its extinction, for instance in mythology. We have several different species of bear, brown bear (Ursus arctos arctos) in Northern Europe and mountainous areas of Southeastern Europe and Western Asia, and Asiatic black bear and sloth bear on the Indian subcontinent. The bear was in prehistoric and historic times spread over a larger area than today (Cooke 2008, 130–133). Scavengers occupy a specific and important role in the ecological system, as they feed on dead animals in their habitat. Our list incorporates one scavenging canid (Canidae), the jackal, mainly targeting the golden jackal (Canis aureus), found in Western Asia and on the Indian subcontinent. In Northern Europe, the corresponding role of the jackal was occupied by the wolf. Most of the animals on our list were known from Greco-Roman antiquity to be the prey of hunting (Pauly and Wissowa 1914, 595–603). Hunting of predators was a prestigious activity, and

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is typically described as performed by heroes in classical sources. Most important is the hunt for the lion, an activity also performed in Anatolia, Western Asia (e.g., in Persian and Babylonian sources), and on the Indian subcontinent. Lion hunting was performed in teams, on horseback (elephants in the East) and on foot, using dogs, spears and arrows. The hunt for bears was more diverse in methods, and involved various forms of traps and snares, poisoned bait, nets, and ambush outside the bear’s hibernating den. Dogs were important in tracking the location of the bear. Battue was reported in antique sources to be performed by bear hunters in the Anatolian mountains, and it was also performed in Northern Europe, according to later sources (Andersson and Granlund 1956, 664–670). A long spear (bear spear) was an important weapon for bear hunting. Common for the entire area where bear was hunted, also in Northern Europe, was the capturing of the cubs alive in order to domesticate them for amusement (e.g., bear dancing). Hunting for the wolf, a much-despised predator, who threated the herding animals, was done over the entire area. As with the bear, wolf hunting was performed by various methods, using poisoned bait, snares, nets, traps; and battue with bow and spear on horseback. The same methods of hunting were used with the fox, which, however, was more valued for its fur, an important trade commodity in antiquity. Scavengers were considered to be a lesser threat to human society than predators. However, they were generally feared and despised for their habit of feeding from the corpses of dead animals and humans (in particular on battlefields). In contrast, they were admired for their intelligence. This goes for the jackal and the wolf, as well as scavenging birds, dealt with in next chapter. The jackal in antique sources was often confused with other similar animals such as the wolf, or the lynx. It was mentioned as an enemy to dogs and lions, and as a “slave” to lions. It was, however, not a threat to humans (Pauly 1921, 399–401). In Indian mythology, the jackal occurs frequently in tales. Because they represent a threat and danger to humans and domestic animals, predators occupy a central role in the rituals and mythologies of the area. However, though being feared and sometimes despised in real life, the position of predators as “royalty” of the animal kingdom often rendered them a prominent position in mythology. Most important, particularly in the Mediterranean, the Near East and on the Indian subcontinent, was the lion, which occupied a specific cultic position in Greco-Roman and Indo-Iranian (as well as Assyrian and Babylonian) mythologies (Gamkrelidze, Ivanov, and Winter 1995, 427 ff.). Here, the lion was a divine and royal animal, a guardian of tombs, cities, and temples, and a protector of power and cosmic order against demons (Pauly 1926, 968–989). The wolf was particularly surrounded by mythology and cultic practice in ancient Indo-European mythologies (Gamkrelidze, Ivanov, and Winter 1995, 413–417). For Greco-Romans, the wolf was a symbol of Apollo, as well as a symbol of the foundation of Rome (as the wolf mother of Romulus and Remus). In Germanic mythology, wolves accompanied the godfather, Odin (Mallory and Adams 1997, 647). The wolf was a frequently-occurring animal in transformation mythology and folklore, and attested in a number of werewolf myths, particularly in Germanic- and Slavic-speaking areas. Werewolf transformations are described also in Greco-Roman sources, in particular so-called “wolf warriors” (Schrader 1929, 667–668). The bear, like the wolf, was already surrounded by mythology and folklore, from antiquity. Like the wolf, the bear occurred in transformation myths, in particular in Germanic and Slavic-speaking areas (Schrader 1923, 81–82), in Caucasus, and in Greco-Roman mythology (Pauly 1896, 2759–2762). Also among Caucasians, the wolf (as well as the bear) plays a central role, being a cultic animal, which was worshipped and personified (Khutsishvili 2010). In Indo-European, all words for predators are characterized by taboo replacements. Beginning with wolf (map 28), we have a common, frequent root, PIE *ulkʷo- ‘wolf’, which is spread over the entire area. In addition we have roots meaning, e.g., ‘the strangler, malefactor’ (PIE *werǵh-e- ‘to strangle’), ‘the howler’ (PIE *waylo- ‘wolf’ < PIE *way- ‘howl’ (symb.)), the ‘sheepkiller’ (PIAr *bhēḍriya- ‘sheep-killer’). Apparently, we witness a cycle of change, where substitution words are created for wolf-words, and where lexemes of the meaning ‘wolf’ again change their meaning back to, e.g., ‘monster’, ‘murderer’, and so forth (see below).

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Figure 14: Borrowability (x), semantic instability (y) and cognacy (node size) for PREDATORS.

In Caucasian languages, wolf roots lead to other animals, mainly of the Canid family, e.g., ‘wolf, hyena, dog’, ‘wild animal’ or ‘ram’ (PKv *mgel- ‘wolf’, PD *gwar- ‘wolf, hyena’; PKv *mqecʰ ‘wild animal’, PD *ħwəčʰ- ‘wolf’; PKv *werʒ- ‘ram’, PNWC *baʒa ‘jackal, hyena’, PN *borʒ ‘wolf’, PD *barc’- ‘wolf’). Taboo replacements are also found among the Indo-European bear words. The ancient, wide-spread bear-word (PIE *h₂rtḱo- ‘bear’) is possibly connected to the root *(h₂)reḱs- ‘to destroy’ (Rix and Kümmel 2001, 505). The Slavic words derive from a compound referring to honey (PIE *médhw-h₁ed- ‘honey-eater’), whereas Germanic word refer to ‘brown’ (PIE *bhero- ‘the brown one’). In Caucasian, bear words lead to ‘badger’, ‘wolf’, and ‘jackal’ (PKv *mačʰw‘badger’, PNWC *maćw- ‘bear’, PN *mčʰar- ‘bear’, PD *məcʰw-, *cʰwəm- ‘bear’; PKv *bragw‘bear’, PNWC *bagw- ‘jackal’, PN *berg ‘wolf’, PD *bagw- ‘badger’). The lion words show a somewhat different pattern: the ancient Indo-European roots (PIE *siHtekó- ‘the maned (one)’, PIE *sinǵha- ‘lion’), were in most languages (including Uralic) replaced by the Greek word, borrowed from Semitic languages (Gr λέων). Noticeable is the Common Caucasian root, which apparently is a metaphorical lexeme (PKv *dew- ‘giant’, PNWC *daw‘great, large, big’, PD *daw- ‘lion’). The other Caucasian terms (see appendix 3b) are apparently loans from either Turkic or Indo-European, but the phonological details are not clear. There are obviously substantial amounts of etymological connections between the large cat words, which cross over language family boundaries (appendix 3b). The connotation networks of colexification and meaning changes (fig. 15a) built by predator concepts in Indo-European are probably among the most interesting in our data. They reflect all the fear, spite, superstition, and taboo; but also the admiration and respect that are built up around these predators in cultures and mythologies. There are differences, though. The predator animals, even though they are found in different climate zones, have mutual connections amongst themselves, but also to other animals, such as whale, giraffe, jaguar, dog. A large and important group of meanings, connected basically to wolf but also to lion and lynx, are humans or human characters with a strong negative connotation, such as villain, monster, malign being, outlaw, criminal, pirate, thief, accursed, or verbs such as to suffocate, to strangle, to kill by violence. In connection to the jackal, these meanings are slightly different, involving deceit and unreliability rather than danger, e.g., cheat, rogue, ill-natured man, coward, poltroon, and in connection to fox, e.g., trickster, cheat, crafty person. The negative connotations continue also among the more casual connections of predator animals, e.g., henchman, vagabond, prostitute, perversion, sin. However, the connotations are not all negative. In connection to lion and bear (as well as wolf) we find meanings such as warrior,

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Figure 15a: Colexification and meaning change for PREDATORS (Indo-European).

hero, or prince. It is interesting to compare to the Caucasian data here (figure 15b). The predator animals bear, wolf, jackal, leopard, and fox (but not lion!), all have mutual meaning changes, but as far as our data is concerned, we do not see the pattern of a metaphoric transfer to human beings with specific (negative) characters that is prevalent in the Indo-European data (fig. 15a). Another noteworthy thing about the predators are the borrowability and instability rates (fig. 14). They have all (except for snake) very low instability rates, completely contradicting the idea of frequent, taboo-related lexical substitution for these terms. Some of the concepts, such as as leopard, lion, jackal and lynx, have high borrowability rates.

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Figure 15b: Colexification and meaning change for PREDATORS (Caucasian).

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Map 28a: Cognacy map for the concept wolf (modern languages).

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Map 28b: Cognacy map for the concept wolf (ancient languages).

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Map 29a: Cognacy map for the concept bear (modern languages).

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Map 29b: Cognacy map for the concept wolf (ancient languages).

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Map 30a: Cognacy map for the concept lion (modern languages).

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Map 30b: Cognacy map for the concept lion (ancient languages).

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Map 31a: Cognacy map for the concept jackal (modern languages).

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Map 31b: Cognacy map for the concept jackal (ancient languages).

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6.4.4 Predator birds In particular scavenging birds, such as the raven, crow, and magpie, were hunted by culling. The raven in Greco-Roman sources was frequently mentioned as a wise bird, capable of telling the future, and a guide (Pauly 1914, 19–23). Roman sources also indicated that the raven in Asia was domesticated for hunting, which had a lower value than the eagle and falcon. In general, the raven was both feared and despised, particularly due to its habit of feeding on corpses on battlefields, a scenario frequently mentioned in Germanic mythology (Andersson and Granlund 1964, 167–173). In Nordic and Celtic mythology, the raven was associated with the god kings Odinn and Lug respectively. Crows were also associated with Celtic warrior-goddesses (Mallory and Adams 1997, 453, Green 1992, 69–70). The eagle had a two-sided function in ancient society: it was considered a dangerous raptor and hunted by bow and arrow and in its nest. It was also, together with the falcon and the hawk, domesticated and used for hunting. The eagle was highly important in Greco-Roman mythology, being Zeus’ symbol and synonymous with the lightning (Pauly and Wissowa 1893, 371–375). Equally important was the owl, Athena’s symbol, frequently occurring in Greco-Roman transformation myths (Pauly and Wissowa 1907, 1064–1071). The scavenging and predator birds, though important in mythology, do not stand out as particularly active in semantic change at least if compared to predator animals (figs. 16, 17). For eagle, we may reconstruct at least two Proto-Indo-European forms (PIE *h₃er- ‘eagle’, PIE *h₂rǵipió- ‘eagle’), but reconstructions also lead to words for bird (PIE *h₂eu-i- ‘bird’). Caucasian etymologies lead to ‘eagle’ as well as to other birds (PKv *orb- ‘eagle’, PNWC *arb-a ‘rooster’, PD *olb- ‘dove’, PKv *arc’iv- ‘eagle’, PN *arc’ib ‘eagle’, PD *barc’im- ‘eagle’). For raven, we have several Indo-European reconstructions (PIE *kor- ‘raven’, PIE *wer, *wor-uo- ‘crow, raven’), a Proto-Uralic term (PU *kulɜ(-kɜ) ‘raven’), and one Caucasian (PKv *ɣred- ‘gannet’, PD *ɣand-u ‘crow, raven’); but several languages apparently substituted their terms by sound symbolic lexemes. Even the reconstructed forms should be seen as partially sound symbolic. The scavenging and predator birds form a natural group of colexifications and meaning changes (fig. 15), distinct from predator and scavenger mammals (fig. 15). Compared to the predator animals, dealt with in the previous chapter, there is a much lower amount of connected meanings, meanings do not generally give negative connotations, and they refer only exceptionally to humans (e.g., owl to witch). An important group of meanings, mainly connected to eagle, contains words related to warfare, e.g., seal, standard, coat of arms. Another group, mainly connected to raven, implies sharp tools or instruments, e.g., pickaxe, mattock. The dark colors are also prominent, e.g., black, dark. There are no specific traces of the owl connecting to wisdom, which is worth noticing. As in several other instances, colexification and

Figure 16: Borrowability (x), semantic instability (y) and cognacy (node size) for PREDATOR BIRDS.

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Figure 17a: Colexification and meaning change for PREDATOR BIRDS (Indo-European).

Figure 17b: Colexification and meaning change for PREDATOR BIRDS (Caucasian).

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meaning change charts inform us about lexical concepts that should have been included, and in the case of predator birds, it is crow.

6.5 Animal husbandry 6.5.1 Domestic animals Domestication of animals involves a controlled spread and thriving of classes and families of animals, in connection to human settlement, which results in man-made breeds and species (Clutton-Brock 1987). Domesticated animal breeds and species can differ significantly in physical appearance from their precursors in the wild, and in particular, their geographic extension is different. Even though most domesticated breeds and species have a single wild species as a precursor, which might be extinct, there are differences, often down to a very detailed level, in the geographic extension of domesticated species. Domesticated breeds and species typically have a specific function in relation to humans: for generations, specific characteristics in domesticated animals have been bred for a specific function in society. We define a number of domestic animals of major importance, which have different histories, relating to pre-Neolithic (Mesolithic), initial Neolithic, as well as to later domestication phases, following different domestication pathways (Zeder 2008). These are the dog, cat, bee, pig, cattle, goat, sheep, horse, donkey, and poultry, which will be closer examined below (6.5.2–6.5.7). Domestication histories of various animals are tightly connected with subsistence. The earliest domesticated animal in Eurasia, predating the agricultural revolution, was the dog (14– 13,000 BP), which was domesticated already by hunter-gatherer populations for the purpose of watching and hunting (Lindblad-Toh 2005, Guagnin, Perri, and Petraglia 2017). The cat also accompanied preagrarian humans early on (≈ 11,000 BP), attracted by the rodent pests of the grain stores of predomestication cultivation (Larson and Fuller 2014). Tightly connected with the Neolithic agricultural revolution is the domestication of the sheep (Ovis aries), goat (Capra hircus) (11,000 BP), pig (Sus scrofa) (10,500 BP), and cattle (Bos taurus) (10,000) (Zeder 2008, Fuller, Willcox, and Allaby 2011, Clutton-Brock 1987). Even though the domesticated species quickly became genetically and morphologically transformed, genetic data suggest a long-term, continuous gene flow between the domesticated animals and their wild counterparts (Larson and Fuller 2014, 118, Scheu 2017). Animal domestication likely occurred according to different principles or pathways (cf. 6.2) (Larson and Fuller 2014, Zeder 2008, 2012). According to the pathway theory, these can be identified as commensal, prey, and directed pathways. The commensal pathway involved a process by which animals that were attracted to human settlements, for instance by pests, waste, or dung, were gradually integrated and domesticated. This was the case with the dog, cat, pigeon, chicken, goose, duck, and likely also the pig. The prey pathway involved a process where animals, originally hunted for their meat, later were integrated as domesticated animals when humans became sedentary. This was the case with cattle, sheep, and goat. Primary products, i.e., the once-in-a-lifetime extraction of products from animals, such as meat, bone, skin, grease, or sinews, were typically the purpose of the initial phase of the domestication, including sheep, goat, pig, and cattle. The extraction of secondary products, such as milk, wool, egg, or power (as draft and carrying animals) developed later, during the Secondary Products Revolution, beginning with the Chalcolithic and Bronze Age in the Near East and Europe (Greenfield 2010). Later domestication histories typically followed the directed pathway, a concept that includes domestication secondary to the agricultural revolution, targeting secondary products. These domestication episodes were later (in some cases) and occured in the fringe or outside of the original domestication area of the agricultural revolution, the Fertile Crescent; such as the donkey (≈ 5,500 BP), horse (5–7,000 BP), bee (≈ 9,000BP) (Roffet-Salque et al. 2016, Larson and Fuller 2014), or various fowls (see 6.5.7).

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6.5.2 Pet animals: dog and cat Today, there are at least 400 breeds of the domesticated dog (Canis familiaris), each of which has a history and a purpose, bred and introduced by humans (Parker et al. 2017). The dog belongs to the family of canids (Canidae), of which there are several species in the wild in our area, such as the wolf, fox, and jackal, which were hunted early on to protect the settlements and domesticated animals (see 6.4.1). The dog was domesticated at least ≈ 15,000 BP from the grey wolf (Canis lupus), with which it is most closely genetically connected among the wild canids (Lindblad-Toh 2005). The geographic origin of the domestication of the dog is not clear, though East Asia has been proposed; the grey wolf, which is today restricted to specific areas due to hunting, was previously found over all Eurasia. The domestication of the dog predates the agricultural revolution and was performed by mobile Pleistocene hunter-gatherer populations (Larson and Fuller 2014, Guagnin, Perri, and Petraglia 2017). The dog was essential to humans in various functions, for which specific breeds were raised. It was used for protecting and guarding settlements, scaring away unwelcome strangers and warning for predators, collecting herd animals and protecting them from predators, tracking prey during hunting, in war, and as company for humans. Already in antiquity, both in the Greco-Roman area, in Egypt, in the Near East, India, and China, humans developed breeds of dogs for specific purposes (Clutton-Brock 1987, 34–45, Pauly 1913, 2540–2554), of which we can distinguish several main types: the sighthound, with light and long legs, aimed for hunting, working dogs, including the tall and heavy flock guards; as well as mastiff-type dogs, used for watching and protecting against predators and enemies. Breeds for animal baiting are also likely to have a long history in the Mediterranean, as do the Far East small-size domestic dogs (Parker et al. 2017). Also in Greco-Roman antiquity, a distinction between in- and outdoor dogs was made. Here, the collar of the dog became important as a marker of the owner of the dog, in specific cases armed by metal and spikes to protect the dog’s neck from bites from predators and other dogs (Pauly 1913, 2555–2558). Early pre-Neolithic depictions of dog hunting in Arabia show dogs stringed to their masters, indicating a very early use of collar for dog-keeping (Guagnin, Perri, and Petraglia 2017). In mythology, the dog and wolf are often confused, resulting in a double role of the dog, which is evident for instance in Greco-Roman belief: on the one hand, the dog is a sacred animal, a protector of house and kin, which is banned as food for ritual purpose. It accompanies several of the gods, such as Jupiter, Apollo, Ares, Hephaistos, and also the hunting deities and heroes, such as Artemis-Diana, or Orion. On the other hand, the dog is also a terrifying guardian of unknown, dangerous worlds, such as Kerberos, the three-headed dog-like creature watching the underworld Hades. In Germanic mythology, the dog accompanies Odin as a hunter during nightly raids. In Indian mythology, corpse-eating dogs and vultures accompany Rudra, the god of wind, storm, hunt, and terror. In Celtic mythology, dogs accompany the death demon Gwynn ab Nudd. In Greco-Roman, Germanic, Old Indic, and Slavic culture, there are parallel myths with the dog as the collector of dead souls; Germanic and Greco-Roman mythologies have parallel myths of the dog as a guardian of the underworld (Pauly 1913, 2579–2581, Schlerath 1954, Green 1992, 82– 84) The cat has a much longer history with humans than previously assumed: it is believed to be commensal (semi-domesticated) already around 11,000 BP, following human settlements, attracted by the mice feeding on human grain stores, but it first became fully domesticated at 4,000 BP (Larson and Fuller 2014). The cat had a less central role to human society than the dog, which is likely also the reason why the cat had a long commensal period of semi-domestication, rather than being immediately bred and domesticated by humans. The semi-domestication, or the behavior of the cat to follow human settlement at a distance, hunting and feeding from waste or rodent pests of households, is probably the reason why cats are scarce in Neolithic archaeological records, and that the genetic difference between wild and domesticated cats are much less distinct than between dogs and wolves (Clutton-Brock 1987, 106 ff.). The domestication of the cat is traditionally sourced in Ancient Egypt, but genetic studies indicate that the cat was

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first domesticated in the Fertile Crescent, and that the Eurasian subspecies of the wild cat, the European wildcat (Felis silvestris silvestris), Near Eastern wildcat (Felis silverstris lybica), Central Asian wildcat (Felis silvestris ornate), and Chinese desert cat (Felis silvestris bieti), each represent distinct lineages of the domesticated cat (Driscoll et al. 2007). The cat is extraordinarily important in Egyptian mythology, but plays a minor role in Greco-Roman mythology (Pauly 1921, 52–57). Interestingly, the cat has a more prominent role in Germanic mythology, as the goddess Freya’s animals and as a symbol for the Jörmungandr serpent (Andersson and Granlund 1963, 362–367). In borrowability, meaning change and cognacy (fig. 18), both dog and cat are surprisingly stable. However, there is an important difference between these two animals, which should be noted. Most cognates for dog (which is a Swadesh term) can be derived to the proto-language of their family (PIE *ḱuōn- ‘dog’; PKv *kʰucʰ-ur- ‘dog, puppy’, PNWC *kʰwəʒ’- ‘wolf’, PN gaǯ-e ‘bitch’, PD *gwəǯ-e ‘dog; bitch’; PKv *ʒaɣal- ‘dog’, PN *c’aq’we ‘snow leopard’, PD *c’irq’o ‘lynx; snow leopard’, PU *pene ‘dog’, PFi *kojra, *kojera). With a few exceptions, such as the IndoAryan substitution words, dog-terms are shared within the families (map 32). A large amount of the cat-words are derived from one widespread early migratory root (proto-form *gat- ‘cat’), also present in Semitic and in Caucasian proto-languages (PKv *k’etha ‘cat’, PNWC *kʰ:at’w: ‘cat’, PN *k’ot’i ‘cat’, PD *k’etʰu ‘cat’). There is no reason to regard this term not to be present at a very early state in proto-languages, in particular considering the fact that the cat likely accompanied already the earliest farming settlements (cf. above). Several terms are clearly sound symbolic innovations, also in the proto-languages (PKv *cʰicʰa- ‘cat (breed)’, PNWC *cʰəcʰă ‘beaver’, PN *cʰicʰ- ‘cat’). Several Uralic languages have later borrowings, indicating that the cat was introduced lately in these languages. Colexification and meaning changes of dog and cat are surprisingly few (appendix 3b). The dog mainly connects to other dog-words, e.g., bitch, pup, or to specific breeds of dog. Only occasionally we find connections to fox, wolf, or negative human beings, e.g., vile person. The contrast to the wolf, the dog’s precursor in the wild, is remarkable (6.4.3, fig. 14) and in particular in the light of the prominent role of the dog in mythology, the high stability of dog words stands out as remarkable. Likewise, the cat has very few colexifications and meaning changes: the only change of importance involves the mustelid animal marten (appendix 3b).

Figure 18: Borrowability (x), semantic instability (y) and cognacy (node size) for DOMESTIC ANIMALS (dog, cat).

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Map 32a: Cognacy map for the concept dog (modern languages).

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Figure 32b: Cognacy map for the concept dog (ancient languages).

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Map 33a: Cognacy map for the concept cat (modern languages).

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Figure 33b: Cognacy map for the concept cat (ancient languages).

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6.5.3 Domesticated insects: the honeybee The precursor of the domesticated bee (Apis mellifera) is found in honeybees, bumblebees, and stingless bees (Apidae), with around 1,000 different species in the wild. The exploitation of the honeybee has a long history, in Eurasia at least from ≈ 9,000 BP in the Near East, and 8,000– 7,000 BP in mainland Europe (Roffet-Salque et al. 2016). The proper domestication of the honeybee is probably somewhat later. In prehistory, the domestication is found in all Western Asia, on the Indian subcontinent, as well as in China. The bee is exploited and later domesticated for the products honey and wax. The main use of honey is to sweeten food, and also to prepare the toxic drink mead (6.7.2), which was drunk already in Neolithic times. Mead was probably a rare and expensive drink, which was complemented and eventually (during the Middle Ages) ousted by other, grain- or grape-based toxic drinks, such as wine and beer (Hornsey 2003, 186 ff.), which also have very long histories (6.7.2). From historical sources, we know of multiple uses for the product wax, such as creating candlelight, preparing metal casting, producing seals or wax tablets. By the middle ages, wax became the most valuable trade commodity besides fur (Andersson and Granlund 1975, 586–590). However, we know little about the main utility of wax in Neolithic times, but a likely use was to cover beverage dispensers (Roffet-Salque et al. 2016). The lexemes for the concept bee show lexical substitution in many languages (cf. fig. 19). For Proto-Indo-European, no specific reconstruction for ‘bee’ can be found, and reconstructions lead, e.g., to the word for ‘honey’ (PIE *meli- ‘honey’), ‘strike’ (PCelt *gʷan-o- ‘to strike’, ‘bee’ < PIE *gʷhen- ‘to strike’), or other insect words (IIr *makš- ‘fly, bee’ (uct. etym.)). Several lexemes meaning ‘bee’ are highly obscure (e.g., CT kro(ṅ)kśe* ‘bee’ (uct. etym.), PItal *api- ‘bee’). We see the same tendency in Caucasian languages (PKv *saxa ‘bee’, PD *śax- ‘beehive’, PNWC *śxa ‘bee’; PKv *bez- ‘wasp; gadfly’, PNWC *bźă ‘bee, wasp’, PD *biz- ‘gadfly’; PKv *sal-u ‘bee’, PN *šal- ‘bee’, PD *šar- ‘bee’; PKv *p’er ‘to fly’, PN *pʰar-lu ‘butterfly’, PD *pʰare ‘bee’). The ProtoUralic form (PU *mekše ‘bee’) is likely a loan from Indo-Iranian (IIr *makš- ‘fly, bee’ (uct. etym.)) (Gamkrelidze, Ivanov, and Winter 1995, 827). In meaning changes, bee connects mainly to other insect-words, such as wasp or beetle, but also occasionally metonymically to bee-hive and honey. Reconstructions that are more straightforward are found with the products of bees, honey and mead. For honey, there are two main Proto-Indo-European reconstructions (PIE *meli- ‘honey’; PIE *kn̥h₂-onḱ-o- < *knh₂- ‘brownish, yellow’). The Proto-Finno-Ugric form (PFU *mete ‘honey, honey drink’) is also a borrowing from Indo-European (PIE *médhu- ‘honey, mead’). Mead is highly intertwined with honey etymologically, sharing reconstructions in Proto-Indo-European

Figure 19: Borrowability (x), semantic instability (y) and cognacy (node size) for DOMESTIC INSECTS (bee).

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(PIE *meli- ‘honey’; PIE *kn̥ h₂-onḱ-o- < *knh₂- ‘brownish, yellow’; PIE *médhu- ‘honey, mead’). Caucasian reconstructions for honey and mead are also intertwined (PKv *muc’- ‘juice of plant’, PN *moc’ ‘honey’, PD *munc’o ‘honey’; PKv *maz-a ‘mead’, PNWC *mzə ‘juice’, PD *maž-e ‘juice’; PKv *cʰux- ‘liquid/juice left after pressing honeycomb’, PNWC *cʰwax- ‘honeycomb full of honey’, PN *čʰuh-i ‘squeeze of cheese’). Wax has a different story. The main Indo-European etymology is derived from a word for ‘to grow’ (PIE *woks-o- < PIE *h₂weks- ‘to grow, become strong’) or ‘to pour’ (< PIE *ǵhew- ‘to pour’). In Caucasian languages, roots lead to ‘wax’, ‘juice’, or ‘bee, beehive’ (PKv *skʰwal- ‘bee; beehive’, PNWC *šakwʰ-a ‘remains of beeswax’; PKv *cʰwil- ‘wax’, PNWC *ćwen- ‘honey; beeswax’, PN *čʰur-ig ‘man-made honeycomb’, PD *čʰwil- ‘wax; honeycomb’). In colexification and meaning change, honey, mead and wine (fig. 36) form a network of connotations: first to other intoxicating drinks (cf. 6.7.2), such as fermented drink, beer, and nectar, but also to abstracts, such as sweetness, delight, and sweet talk. Only indirectly, there is a connection to wax (appendix 3b), which itself has few connections, including candle. However, note that we have classified bee different from honey and wax (products), which we in turn have classified differently from mead (drink and drugs). This is because of their different scores in borrowability and semantic instability (6.7.3).

6.5.4 Pig raising Even though it has been suggested that the earliest domestication of the pig (Sus domesticus) might have been commensal, with wild boars following human settlements and feeding on their waste, it is generally believed that the domestication of the pig was simultaneous and similar to the domestication of goats, sheep, and cows, following the prey pathway (Larson and Fuller 2014). The domestication of pigs, like goats, sheep and cows, required a settlement with plant cultivation and was done by the early farmers in Southeastern Anatolia ≈ 10,500 BP (Zeder 2008). By this time, people deliberately began to control the offspring by killing the young males and keeping the females in order to maximize meat production. Genetic studies indicate that domestication of pigs occurred independently in several locations, such as South East Asia, Anatolia, and China, and that there was a continuous interbreeding with wild boars (Larson and Fuller 2014, Vigne 2011). In Western Eurasia, the domestication of pigs followed oak woodland zones, indicating that pigs were kept loose rather than in closure (Larson and Fuller 2014), even though pigs are impossible to herd and thus useless for pastoralist societies (Mallory and Adams 1997, 428). The main purpose of pig domestication was meat production, for which these animals are highly appropriate: compared to cattle, pigs are efficient meat producers (equivalent to sheep and chicken), capable of producing more protein and fat on lesser water and food (Steinfeld 2006). Pigs can also feed on human waste, including other meat, something that must have made them invaluable as a reliable food source. It is obvious that pigs were an important food source to most ancient Indo-European populations in Western Europe and Mediterranean, though among early Semitic populations in Western Asia and on the Arabian Peninsula, a decline in pig consumption arose already in antiquity. Pigs are also very unusual in Ancient Egyptian depictions (Pauly 1921c, 801–804). However, the domesticated pig is absent in archaeological evidence from the early records in Central Asia, including the areas connected to Proto-Tocharian and Proto-Indo-Iranian (Andronovo and Afansievo). Here, the domesticated pig was first introduced during the Bronze age (Mallory and Adams 1997, 425). Like the dog, the mythological associations of the pig are multi-sided, both good and sinister, and associated with the wild boar (Gamkrelidze, Ivanov, and Winter 1995, 510–511). In IndoEuropean religions, including Germanic, Celtic, Greco-Roman, Hittite, and Vedic, the pig, or boar, is an animal associated with warriors, heroes, and kings. The pig also is often, similar to the dog, a mysterious animal, associated with the otherworld, the supernatural, and the dead; on

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Figure 20: Borrowability (x), semantic instability (y) and cognacy (node size) for PIG RAISING.

the other hand, it is also associated with fertility, vegetation, the sun, the sky, and festivities (Mallory and Adams 1997, 426). In Greco-Roman mythology, the pig is a frequently sacrificed animal, offered to all gods, an in particular to Demeter for crop and fertility. It is also sacrificed in chthonic sacrifices, to Persephone, to conciliate the gods of the underworld (Pauly 1921c, 811– 815). Pigs play a prominent role in Celtic and Germanic mythology, in particular as meat at festivities, as in the Irish story of Mac Da Thó’s pig. To the ancient Celts, the pig, through the god Moccus, was the most sacred animal. Among Celtic myths we also have the tale of Mag Mucrime, lethal pigs from the underworld, which ravage the lands, paralleled by the Scandinavian myth about the red-eyed, ravaging pig from the underworld, the Gloso, with parallels in Northern Europe, e.g., Germany (Bächtold-Stäubli and Hoffmann-Krayer 1927, 7, 1476). In Germanic mythology, the pig has a role as symbol of the fertility gods, Frey, and Freya. Further, the myth about the never-ending pig, which can be eaten and on which the flesh grows back again every night, is paralleled in Celtic and Germanic mythology (Mallory and Adams 1997, 428). Pig raising words are low in borrowability but relatively high in semantic instability (fig. 20). In Indo-European languages, words for pig (including sow), piglet and boar are rich in etymologies, of which many are intertwined. There are two main Proto-Indo-European reconstructions with the meaning ‘pig’ (PIE *suH- ‘pig’, PIE *porḱo- ‘young pig, piglet’). Besides, the branch proto-languages, e.g., Proto-Celtic and Proto-Germanic, show substituted terms (PGm *galtan‘boar’ < *gald(j)a- ‘infertile’ < PIE *ghol-tó-; PCelt *mokku- ‘pig’ (uct. etym.); PCelt *krākni- ‘sow’ (symb.)). As with several of the younglings of the larger domestic animals, words for piglet lead to roots with a general meaning ‘young of animal’ (PIE *pōr-o- ‘young of animal’ < PIE *per- ‘to give birth’). For Caucasian languages there are several pig roots (PKv *ɣor- ‘pig’, PNWC *ɣaw‘pig, piglet’, PN *eɣ-ə ‘pig’; PD *bol’- ‘pig’, PKv *burw- ‘gilt (female pig, 3–12 months old); suckling pig’, PNWC *bl˜’-ə ‘sow, female pig’, PN *borl’- ‘colourful’), but the piglet reconstruction is intertwined with sheep/lamb (PKv *znaɣ-a ‘lamb’, PNWC *źaɣă ‘sheep’, PN *žarɣ-a ‘pig’, PD *žaq’-a ‘piglet’). In Uralic, the Proto-Finnic root *sika ‘pig’ is likely a borrowing from Indo-European, but the details remain unclear. The root PFi *porśas, *porćas is loan from Indo-Iranian (Gamkrelidze, Ivanov, and Winter 1995, 815). The pig and (wild) boar words are highly connected in terms of meaning change and colexification (fig. 21a–b). There are some differences, though. Besides various pig words (sow, solitary pig), pig connects to humans with negative connotations, such as fat person, greedy person, filthy person, whereas boar connects to meanings such as powerful, ruler, manly, husband. Occasionally, pig connects to other animals, such as stallion, elephant, goat, calf. This also recurs in Caucasian languages, where we find connections with pig such as sheep,

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Figure 21a: Colexification and meaning change for PIG RAISING (including WILD BOAR) (IndoEuropean).

Figure 21b: Colexification and meaning change for PIG RAISING (including WILD BOAR) (Caucasian).

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lamb, and with wild boar, e.g., camel (fig. 21b). Typically, the connection is through young animals of any domesticated animal (cf. Indo-European, fig. 21a).

6.5.5 Bovine cattle and dairying Under this heading, we deal with the domesticated bovine animals as well as the resulting dairy products (cf. also 6.5.8). Bovine cattle (Bos taurus) were domesticated first in the Upper Euphrates Valley, between 11–10,000 BP (Zeder 2008) from the aurochs (Bos primigenius). The Zebu cattle (Bos Taurus indicus) was domesticated in the Indus Valley between 9,000–7,000 BP, either from taurine animals imported from the West, or by independent domestication of wild Zebu. The river and swamp buffalos (Bubalus bubalis) were also domesticated in the Indus Valley by 4,500–4,000 BP, from wild cattle (Larson and Fuller 2014). All bovine cattle domestication followed the prey pathway, where animals were first hunted for their meat and later domesticated. It is likely that cattle were originally domesticated only for the purpose of meat (and skin), and that dairying developed later, beginning in the Fertile Crescent around 8,500 BP. The early Neolithic farmers were unable to drink fresh milk and they reduced the lactose concentrations in the milk by developing secondary products, such as cheese and yoghurt. The development of milkdrinking and subsequent lactose tolerance emerged 7,500 years ago among Neolithic farmers in Central Europe, a mutation that is believed to have been demographically successful. Because of this mutation, lactase persistence is still today concentrated in Northwestern Europe, with other epicenters in West Africa and on the Arabian Peninsula (Curry 2013, Greenfield 2010). The domesticated cattle were tamed from the wild aurochs, which continued to be hunted until it became extinct in the Middle Ages. Depictions and archaeological data from Bronze Age and Antique Europe, Anatolia, Caucasus, and Western Asia indicate that the aurochs, beside the wild bison in Western, Southern, Eastern Europe and Caucasus, was a frequent and important hunting prey animal (Mallory and Adams 1997, 136). The domesticated cattle were significantly smaller than their wild counterpart was. From the earliest period of domestication, bovine cattle must have been useful for various purposes, most importantly meat production and dairying. Cattle also became important as draft animals, in particular with the invention of the plow, a continuation of the hand-held hoe (draft by an animal). This technique likely developed first in the Near East around 7–8,000 BP, and is later attested in various sources (archaeological evidence, depictions, pictograms) in the Mediterranean, Western Asia and Northern Europe (5,500– 5,000) and on the Indian subcontinent (Mallory and Adams 1997, 435) (cf. 6.6.3). The occurrence of castrated animals in archaeological records is a sign that bulls were used as oxen, with the main function of being draft animals, which is widespread towards the end of Neolithic times. In all ancient Indo-European cultures, the cow was the most highly valued animal, used as means of payment, e.g., for dowry (Schrader 1929, 253–254). Another aspect indicating the cultural importance of the cow is the high value of its milk. Milk from other animals, such as goat, sheep, and horse, was also extracted, but the cow remained the the most important source for milk. Secondary products, e.g., butter, cheese, and yoghurt, were prepared, which show a large amount of local variation. Cows, bulls, and oxen play important roles in ancient mythologies. The cow is seen as a highly sacred animal, the killing of which is unavoidable and has to be ritualized in various ways. This scenario is described in Greco-Roman sources, as well as in the Old Indic, Old Iranian, Anatolian, as well as Egyptian tradition (Pauly 1929, 2502 ff., Gamkrelidze, Ivanov, and Winter 1995, 488 ff.). We also have the tradition of the cosmic ‘proto-cow’, capable of producing enormous quantities of milk, e.g., Auđhumbla in Germanic mythology, the mighty ‘wish-cow’ Kamadhenu in Old Indic mythology, and Fuwch Gyfeilioru, the healing, powerful cow in Celtic mythology (Mallory and Adams 1997, 137). A general Indo-European tradition is the cow-sacrifice, for which there is a term in the proto-language, *ḱṃto(m)-gʷwo- ‘the sacrifice of a hundred cattle’. Beside the horse sacrifice (see 6.11.1), cattle sacrifice is most important sacrifice among Old Indi-

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an, Hittite, and Greco-Roman populations (Puhvel 1978). A frequent myth in ancient Indo-European religions is cattle-raiding, as in the Celtic Táin Bó Cúailnge ‘the stealing of Cooley’s cattle’, which is paralleled in Old Indian and Greco-Roman myth (Mallory and Adams 1997, 138–9, Green 1992, 51–52). The cow was also a symbol for settlement, e.g., in Greco-Roman mythology the foundation of cities was done by a ritual furrow plow by an ox (Pauly 1929, 2503–04). The milking and milk, generally a symbol for richness and abundance, is prominent in most ancient IndoEuropean mythologies, in particular among Indo-Iranian populations. Ancient Romans, paralleled in Old India, performed sacrifice of milk and milk products (Schrader 1929, 64–65). The entire complex of bovine cattle keeping, milk and milk products is well reconstructable to Indo-European, with a large amount of secure etymologies (Garnier, Sagart, and Sago 2017). We will deal with the related etymologies here, but in our classification, we have split bovine animals into two categories, cattle and draft animals, and the milk under products, due to their difference in behavior (6.7.3). Bovine words are highly intertwined in etymology as well as in semantic change (see below). There are several important and frequent roots in Indo-European, both with the meaning ‘cow’, ‘bull’, ‘ox’, ‘calf’, and ‘cattle’ (PIE *gʷeh₃-u- ‘cow’, PIE *h₂eǵHo- ‘cow’, PIE *peḱ-u- ‘cattle’, PIE *gʷh₃urs-en- ‘male bovine’, PIE *Huks-en- ‘ox, young bull’, PIE *tawro- ‘bull, aurochs’, PIE *ḱer(h₂)-uo-/-ueh₂- ‘horned animal’, PIE *dmh₂o- ‘tamed animal, ox’, PIE *ueḱ-eh₂, *uoḱ-eh₂ ‘bovine, cow’, PIE *wetso- ‘young of animal’ < *wet- ‘year’, PIE *gʷelbh-u- ‘young animal, womb’). In Caucasian languages we also have a set of stable roots for the bovine animals, for bull (PKv *k’as- ‘pig (m., uncastrated)’, PD *k’eš-a ‘bull’; PKv *gen- ‘calf’, PD *gan- ‘bull’), for cattle (PKv *cham-e ‘cattle’, PNWC *čam-ă ‘cow’, PD *čwaʰm-a ‘sheep’; PKv *xwar- ‘holy, sacrifice cattle’, PNWC *xwar-a ‘horse (thoroughbred)’, PD *xwar- ‘horse, mare’; PKv *req’- ‘driving of cattle’, PD *req’w- ‘herd (of cattle)’; PKv *buc’- ‘shearling lamb (6–12 months old); female pig, goat or sheep’, PD *buc’-ir ‘sheep’), for cow (PKv *ʒuwe ‘breast’, PNWC *ʒ’wə ‘cow’, PN *ǯwawo ‘cow’, PD *ʒinwo ‘cow’; PKv *gom- ‘cattle-shed, cow-house’, PNWC *gwəm-a ‘cow’, PD *gum-a ‘pig’; PKv *ʒrux-a ‘cow’, PD *ʒunχw-a ‘cow’; PKv *cʰur- ‘udder’, PNWC *čʰʲər ‘udder; milk’, PD *čʰur‘cow; meat’), and for ox (PKv *bacʰ- ‘ox; cattle defender deity’, PD *bacʰ- ‘ox’, PN *bstʰu ‘ox’; PKv *qar- ‘bull, ox’, PN *ħal- ‘cow’, PD *ħan- ‘ox’; PKv *k’ur- ‘stallion’, PD *k’or- ‘bull’; PKv *macʰ-al- ‘buffalo (young)’, PD *mačʰ-or- ‘calf; buffalo (young)’; PKv *ɣoɣo ‘buffalo (young, up to 1 year old)’, PD *ωoq-a ‘calf; buffalo (young)’). Etymologies for the wild precursor of bovine cattle, the extinct aurochs and bison, are more complex. There is a proto-form of uncertain derivation and origin, which is spread in most IndoEuropean languages (proto-form *uisond-, *uisondh- (uct. etym.)). Caucasian terms are intertwined with etymologies for other wild animals (PKv *bul-a ‘big forest-dwelling creature; male sheep’, PNWC *bələ ‘ram; cattle’, PN *bul-a ‘wild cattle, bison’, PD *bol-e ‘antelope; cattle’). The entire group of cattle is complex in terms of borrowability, semantic instability and cognacy (fig. 22). Accordingly, colexification and meaning change connections of bovine words in our data are abundant. Both reflect the high importance and value attributed to these animals (see 6.13). The game animal bison has a marginal role, and with one exception (deer), it connects only to other bison terms, such as aurochs and wisent. The domestic bovine network is huge, and in this evaluation we have to focus on the core parts, i.e., meanings that form clusters or that are nodes of meaning networks. The network reveals some of the important functions of cattle (fertility, wealth, traction, farming), whereas other important functions are invisible (milking and meat production). First, we have various stray connections to other wild and domestic animals, such as goat. Nodes of animal words in the network include beast, animal, herd, livestock, sheep, stag, boar. Besides, we may identify several important semantic clusters, which indicate core functionalities of bovine animals. First, we have the important cluster of meanings connecting to wealth and money (mainly by cattle), including money, goods, treasure, wealth, fortune, possession, property, tax, tribute, which is itself connected to meanings such as ruler, husband, powerful, manly (mainly with bull, cattle). Further, we

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Figure 22: Borrowability (x), semantic instability (y) and cognacy (node size) for CATTLE.

have metaphoric node meanings such as bride and fool. Another group contains metonymic meanings referring farming as an activity, which are spread all over the network, e.g., arable land, produce of the land, to cultivate, stable. A smaller cluster of meanings refer to the role (of primarily bull) as fertilizer, such as brood, fetus, offspring, fruit, but also penis, limb, testicle. We find connections that indicate the function of traction, e.g., strong, firmness, to plow. Only as an exception (individual cases) we find meanings connecting to the most important products of bovine cattle, dairying and meat production, by meat and butter (milk is not attested at all). This is noteworthy, considering the fact that we frequently find metonymic connections between the producing animal and the product elsewhere in our data. We include the product milk under the heading of ‘bovine cattle and dairying’ (for meat, see 6.5.8, for the classification products see 6.7.3), therefore, we deal with the milk words and the milk network here. There are at least two Proto-Indo-European words which target (cows’) milk (PIE *glg-t- ‘milk’; PIE *h₂melǵ- ‘milk’). Caucasian languages also have several roots for milk words, with various connected connotations (PKv *mzel- ‘milk’, PNWC *băžə ‘milk’, PN *maša ‘milk food’, PD *maz ‘boiled, fermentable milk’; PKv *švra- ‘whey’, PN *šura ‘milk’, PD *sura ‘milk product’; PKv *sʒe ‘milk’, PNWC *ra-ʒa ‘to filter, to strain’, PD *-erǯ- ‘to milk’). In terms of colexification and meaning change, milk connects to other dairy products, such as cheese, to other fluids, such as juice, tears, but also to meanings signaling fertility, e.g., virgin, girl, pregnant, to nursing, e.g., children, or to abundance, e.g., fat, abundant.

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Map 34a: Cognacy map for the concept bull (modern languages).

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Map 34b: Cognacy map for the concept bull (ancient languages).

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Figure 23a: Colexification and meaning change for CATTLE (including bison) (Indo-European).

Figure 23b: Colexification and meaning change for CATTLE (including bison) (Caucasian).

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Map 35a: Cognacy map for the concept milk (modern languages).

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Map 35b: Cognacy map for the concept milk (ancient languages).

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Figure 24a: Colexification and meaning change for the concept MILK (IndoEuropean).

Figure 24b: Colexification and meaning change for the concept MILK (Caucasian).

6.5.6 Pastoral activities: sheep and goat Besides bovine cattle, sheep and goats are important pastoral animals, domesticated for meat and the secondary products milk and wool (for sheep). The domestication of sheep and goats belong to the earliest phases of the Neolithic revolution ≈ 11,000 BP in the Near East and Levant, predating both pig and cattle (Zeder 2008). The domestication of sheep (Ovis aries) and goat (Capra hircus) followed the prey pathway, where the wild progenitors, in the case of sheep the Asiatic mouflon (Ovis orientalis), and in the case of goats to the Bezoar goat (Capra aegagrus), were first hunted for their meat, and then only the males were killed and eaten and the females kept for reproduction (Clutton-Brock 1987, 52–61, Mallory and Adams 1997, 510–512, Zeder 2008,

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Larson and Fuller 2014, Scheu 2017). During the Secondary Products Revolution of the Chalcolithic period, sheep were domesticated for the purpose of producing wool (6.5.9), but sheep and goats were also domesticated for the purpose of milk (Greenfield 2010). In general, the keeping of what is often referred to as ‘small livestock’ can be either complementary to bovine cattle and pigs (6.5.4–6.5.5), but it is also, in some cultures, the main subsistence source, something which occurs sporadically over our entire area. An important aspect is that the practice of pastoralism of sheep and goat can be exerted in environments (e.g., mountainous areas), which are otherwise unsuitable for more large-scale agriculture. For this reason, in prehistory as well as today, the practice of sheep and goat pastoralism are often found in pockets and niches between more large-scale agriculture areas, with farmed land and large livestock, where pastoralist niche cultures typically interact with their agriculture neighbors, for instance by trading of wool (Halstead 1996). Since in particular sheep, as well as goats, are often herded rather than kept in enclosures, the domestication of sheep and goat is also connected to the domestication of the dog, which was already in the earliest phase of domestication used as an aid for herding of small livestock (6.5.2). It is worth noticing that small livestock, compared to cattle, pigs, and horses, play a much less prominent role in Indo-European mythology and sacrificial practices. Nevertheless, a complete terminology of small cattle is reconstructable to the proto-language (Mallory and Adams 2006, 134–143, Pinault 1997). Sheep and goat are used as sacrifice animals both in Greco-Roman and ancient Indo-Aryan practice, but is also referred to as of lower value as a gift to the gods, compared to, e.g., bovine cattle (Mallory and Adams 1997, 510–512). First, for the younglings (kid, lamb), there is a lot of etymological intertwining, which also goes beyond the small cattle domain (see below). Beginning with goat, we have several common roots in Indo-European, both with the meaning of ‘goat’ and ‘buck’. Several of them might be considered as early migration words or substrate loans, but the details remain unclear (PIE *bhuǵo- ‘goat, buck’; PIE *kapro- ‘buck, hegoat’; PIE *h₂eǵ-ino- ‘goat, goat skin’ (migr.?); PIE *ghaid- ‘goat’ (migr.); proto-form *kō̆g(h)(uct. etym.)). Caucasian languages have a set of goat etymologies, which are intertwined with other small cattle etymologies (PKv *a-ʒman- ‘sheep (2 years old)’, PNWC *ǯman- ‘goat’, PD *ǯama ‘goat (2–3 years old)’; PKv *westʰ- ‘kid’, PNWC *stʰăw- ‘goat’, PN *wastʰ- ‘goat (1 year old)’; PKv *wacʰ- ‘he-goat’, PNWC *wač-ă ‘male goat’, PD *ωečʰa ‘goat’; PNWC *tʰwəɣ-a ‘he-goat; ram’, PD *tʰeωw- ‘sheep (m.)’, PK *tʰiɣ-, *tʰeɣ- ‘sheep (m., uncastrated); lamb’, PN *tʰaɣ- ‘male’; PNWC *bək’w- ‘calf’, PKv *bok’w- ‘billy-goat’, PN *bok’ ‘billy-goat’; PKv *c’al- ‘billy-goat’, PNWC *ʒa- ‘kid goat’, PN *c’in- ‘ram (for slaughter)’, PD *c’an- ‘goat’). For the sheep words (sheep, ram, lamb), we have several central Indo-European reconstructions (PIE *h₃éu-i- ‘sheep’; PIE *uerh₁-u- ‘sheep, lamb’; PIE *urh₁-en- ‘lamb’; PIE *h₂wŕ̥s-en‘male’; PIE *h₁er- ‘lamb, kid’; PIE *h₂egʷno- ‘lamb’). In Caucasian, lamb and goat etymologies are intertwined (PKv *rit’el- ‘goat’, PD *rit’an- ‘lamb’, PNWC *t’ă- ‘ram’; PKv *k’raw- ‘lamb’, PD *k’war-a ‘lamb; bullock’, PN *k’orn- ‘offspring of domestic animals’; PKv *warq’-a ‘milk mushroom’, PD *baq’ar-e ‘lamb; sheep’, PN *baq’-o ‘colt’; PKv *ne-rb- ‘breeding ewe, coire’, PNWC *abə ‘he-goat, male goat’, PN *ħalb- ‘lamb’, PD *nemb- ‘sheep’; PKv *xul- ‘sheep (breed)’, PN *axwar- ‘lamb’, PD *ənxwa ‘sheep’, PNWC *xwə- ‘sheep’; PKv *cʰxw-ar- ‘sheep’, PN *čʰux-i ‘lamb’, PD *čʰaqu- ‘lamb; sheep’; PKv *zwar- ‘calf’, PN *žawr- ‘sheep; flock of sheep’, PD *luž-, *žwal- ‘flock (of sheep); livestock’; PD *tʰeωw- ‘sheep (m.)’, PKv *tʰiɣ-, *tʰeɣ- ‘sheep (m., uncastrated); lamb’). Interestingly enough, lexemes for small cattle are much more stable in terms of borrowability, semantic instability and cognacy compared to cattle (fig. 22). These words are also relatively modest in colexification and meaning change (see appendix 3b).

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Figure 25: Borrowability (x), semantic instability (y) and cognacy (node size) for SMALL CATTLE.

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Map 36a: Cognacy map for the concept sheep (modern languages).

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Map 36b: Cognacy map for the concept sheep (ancient languages).

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6.5.7 Wool production Like the procedure of milking (6.5.5) and the use of farm animals for transport and labor (6.11.1), wool production belongs to the Secondary Products Revolution of the Chalcolithic period (7,000– 6,000 BP). A central issue in establishing a date for the beginning of wool production is to identify when the domestication of sheep started to breed in a direction of finer wool types, in contrast to the hair or kemp of wild sheep, which is hardly spinnable (Barber 1991, 20–30). This evolution likely started in the Chalcolithic Near East and Mesopotamia. From the same period, archaeological and pictographic data also indicate the use of spindle-whorls for spinning (Greenfield 2010, 35 ff.). From 6–5,000 BP, there is an increase in wool sheep in all archaeological sites in Europe, indicating an industrial production and trade; wool trade is particularly important in Linear B sources (Mallory and Adams 1997, 648–649). The main purpose of wool is textile production (6.8.2), and besides flax, wool remained, within our area, the most important domesticated product aiming at this purpose. The processing of wool for producing textiles and clothes is connected to a large number of techniques and technologies, which developed by and after the Secondary Products Revolution. This includes, for wool, shearing and combing. Within Indo-European, plucking seems to be another important process of extraction, used instead of combing to prepare the wool for spinning (Barber 1991, 261). The following step in textile production is to spin the wool for producing thread. The final process is fabric and cloth production, where an alternative process, to weaving, namely felting, was used for wool (6.7.2). There is one dominant Indo-European root for wool (PIE *h₂ulh₁- ‘wool’). There are more reconstructed roots (PIE *ueru-os- ‘wool’), as well as some parallel tracks, but in principle, wool has very little lexical substitution (map 37). We see a similar development in Caucasian languages (PKv *las- ‘soft, thin wool’, PNWC *laśw- ‘wool’, PN *ħas- ‘woolen threads’, PD *lăns ‘hair; autumn wool’). Most Uralic terms are loans from Indo-European PIE *h₂ulh₁- ‘wool’ (see appendix 3b). For the borrowability, semantic instability, and cognacy of wool, see 6.7.3. The colexifications and meaning changes of wool words (appendix 3b) are restricted, which is interesting in contrast to the abundance in meanings of other products, such as grease and meat (6.5.8), as well as the instruments to prepare clothes (6.8.2). Wool connects to wool products, e.g., fleece, cloth, but also hair, fur, by metonomy to cattle, ram, sheep, as well as to property, money.

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Map 37a: Cognacy map for the concept wool (modern languages).

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Map 37b: Cognacy map for the concept wool (ancient languages).

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6.5.8 Poultry The domestication of fowl is considerably later than the domestication of dog, sheep, goat, and bovine cattle. In general, the domestication of fowl most likely followed the commensal pathway, with birds following human settlement, feeding from the waste or the stubble of harvested fields (Larson and Fuller 2014). Domesticated fowl of our area includes pigeon (Columba livia), chicken (Gallus gallus), duck (Anas platyrhynchos), and goose (Anser anser). Adaptation of pigeons occurred first in the Near East, when birds moved from their mountain habitats to human settlements, probably as early as ≈ 5,000 BP, and become domesticated in the area during historical periods, ≈ 3,000 BP. Adaptation of chicken to human settlement began in Southeast Asia, probably as early as 6–5,000 BP in the Indus Valley, with domestication around 4,000 BP (Cooke 2008, 254). The domestication of the goose and the duck is also late. In Europe the domestication of the goose, from the wild graylag goose, first began in the Greco-Roman era, but sources indicate that the goose was domesticated in ancient Egypt earlier than that, around 5,000 BP (Schrader 1923, 339–341). Simultaneously, there was an independent domestication of the goose in East Asia. A commensal period of geese following human settlement likely preceded the domestication by about 2,000 years. We have a similar situation with the duck (Anas platyrhynchos); at least in East Asia. In Europe, domestication of the duck began first by the Middle Ages (Larson and Fuller 2014). Wild greylag goose (Anser anser) is found in restricted areas from British Isles to the Indian subcontinent, the wild duck (Anas platyrhynchos) is found over the entire area, whereas the red junglefowl (Gallus gallus), the wild precursor of chicken, is inherent in Southeast Asia only (Cooke 2008, 254–259). Domesticated fowl were kept both for meat, grease, and egg production, for which they are well suited. Besides pork, chicken meat is highly cost-effective and chickens are capable of producing meat in a short time. In the Greco-Roman period, goose was an attractive meat for feast occasions, and the meat and grease was used for medical purposes. Furthermore, goose feathers were used to produce cushions and pillows (Pauly 1910, 709–734). The medical use of goose is also reported from Northern Europe in the Middle Ages (Andersson and Granlund 1960, 684– 689). The lexical group poultry cannot with certainty be reconstructed to Proto-Indo-European. There are several problems, first the high degree of lexical substitution, leading to a vast number of different etymologies, second the high amount of apparent sound symbolic terms in the languages, including among the reconstructed forms. For details, we refer to appendix 3b. The patterns of Indo-European also recur in Caucasian languages. We also have a certain degree of borrowability, e.g., for chicken, as well as semantic instability (fig. 26).

Figure 26: Borrowability (x), semantic instability (y) and cognacy (node size) for POULTRY.

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6.5.9 Animal products Under this heading, we include two concepts of our data, meat and grease. These products, which were extracted from both domestic and game animals (grease mainly of fat animals such as goose and pig) were of substantial importance and filled a crucial function in the diet, grease particularly in colder climates. As for etymologies, we may reconstruct words with the meaning ‘fat’ and ‘grease’ to the proto-languages, both for Indo-European (PIE *smer- ‘fat, grease, tallow’; PIE *poih₂-o- ‘fat’; PIE *h₃engʷ-en- ‘butter, fat’) and Caucasian. However, there is a high degree of lexical substitution and many different parallel tracks (see appendix 3b). The enormous size of the colexification and meaning change network of these two concepts (fig. 27), grease and meat, is indicative both of the importance as well as the multitude of functions of animal food products. First, the network provides us with a large number of extra nodes, including concepts such as fat, tallow, suet, lard, oil, pork, flesh, ointment. These meanings connect grease and meat. Apart from this, grease and meat fall into two main categories, where meat has mainly negative connotations and grease mainly positive connotations. For meat, we have meanings referring to the corporeal origin of meat, including blood, gore, raw, leading to negative connotations such as cruel, rough, ungodly, moist. Furthermore, we have body, breast (female), corpse. Grease, on the other hand, connects to positive concepts such as richness, fatness, smooth, fertile, but also to intestines, e.g., entrails, kidneys.

Figure 27a: Colexification and meaning change for MEAT and GREASE (IndoEuropean).

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Figure 27b: Colexification and meaning change for MEAT and GREASE (Caucasian).

In our classification, we have grouped meat and grease with materials, which includes fur and other products of (mainly) hunting, slaughtering or other processing that involves more forceful preparation. This is due to their significantly different behavior in contrast to the other food products (see 6.7.3).

6.6 Agriculture 6.6.1 Introduction The dominant subsistence system of our area, plow-based agriculture, originally emerged in Southwest Asia, i.e., the Fertile Crescent and Anatolia, 10–11,000 BP (Zeder 2008) and then spread from this area, gradually or in bursts, to the north, northwest, and east. The original spread of agriculture, an entirely different subsistence system, gradually and subsequently replaced foraging, but it is likely that the transition was a parallel evolution, emerging from several epicenters of the initial area, rather than a revolution, emerging from one single epicenter (Larson and Fuller 2014). Hunter-gatherer populations continued to exist side by side with agriculturalists for a long period: not until 5,000 BP was agriculture (and pastoralism) the dominant system of all Eurasia (Page et al. 2016). There is a rich literature and several competing theories on the emergence of agriculture (Barker 2006, 1–41) and recent progress in archaeological research has significantly increased our knowledge of the time, place and cause for this development. There were two main agricultural revolutions, which made a permanent impact on the living conditions and cultural systems of prehistoric people: the initial Neolithic Revolution, involving the domestication of distinct wild species of plants and livestock, which was concentrated to the area of the Fertile Crescent and Anatolia, and the Secondary Products Revolution, involving a large-scale secondary exploitation of domesticated plants and livestock. In particular the Secondary Products Revolution was more of several independent, parallel evolutions than one single revolution: various types of exploitations emerged over a large area, where the practice of domestication and cultivation had become the prevalent subsistence system. This lead to numerous innovative changes during the Early Chalcolithic period (Greenfield 2010). Agriculture as subsistence, including all exploitative innovations of the Secondary Products Revolution (see 6.5.7, 6.5.9, 6.11.1), continued to play a prominent role in most societies over the entire area. However, local

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cultures of dependence on pastoralism persisted, particularly in areas where difficult environmental conditions such as cold climate, unusable soils, or mountainous settings constrained agriculture. The spread of agriculture, including the domestication and further breeding of livestock and the cultivation of cereals and vegetables, lead to an adaptation to changing environmental preconditions. In Western Asia, agriculture had to adapt to various landforms: mountain ranges, alluvial valleys, semi-arid steppes, and deserts, where the rainfall increases steadily towards the east. The alluvial plains of Northern India turned out to be highly fertile, but the northeast of India is tropical, giving rise to different systems within this continent. The ‘Eurasian’ farming system dominated in Western Asia, where crops are sown in winter/autumn and harvested in spring and the cultivation of grain and vegetables is integrated with the domestication of livestock. In colder northern climates, as in Scandinavia and Northern Europe, crops were sown in spring (in northern Scandinavia even in early summer) and harvested during the summer. During the Middle Ages a practice of sowing in winter and harvesting in spring was initiated for cold-resistant cereals, such as rye (Andersson and Granlund 1972, 660–663). In Southeast Asia, the agricultural system made use of the summer monsoon rains. Crops were sown in spring and harvested in the autumn, taking advantage of the wet period. Rice was the main summer crop, in addition to other crops, such as millet and pea (Barker 2006, 149–150, 178). The spread of farming into Europe has been the source of intense scientific debate for years, and recent advancement in ancient DNA technology has shed new light on old questions. An old controversy on the spread of agriculture involves the manner in which it was spread. According to the proponents of the “wave of advance” theory, agriculture spread gradually by acculturation, rather than by colonization, from Anatolia towards Northern, Central, and Eastern Europe (Ammerman and Cavalli-Sforza 1971). However, this theory is refuted by a number of complicating factors, such as the age and status of very early Neolithic sites in Europe. These indicate a more complex spread, which involves punctual evolutions, spread of diseases, and colonization (Barker 2006, 325–328, Lipson et al. 2017, Andrades Valtueña et al. 2017). An important factor impacting agriculture in Europe – in particular in the northern parts – was climate changes caused by deglaciation. More or less “modern” temperatures during the period 12,700–10,800 BP changed towards a significantly colder climate during the period 10,800–9,600 BP, and returned to “modern” temperatures during the Holocene. The climate changes were swift and often gave rise to extreme conditions, such as a drastic rise of the sea level between 11,000 and 8,500 BP. With the increase in temperature, wild species radically changed their habitat, moving northwards and westwards. Compared to the arctic tundras of Pleistocene, with flocks of mainly reindeer and horse, early Holocene Europe had a rich diversity of flora and fauna, including mammals such as beaver, otter, hare, fox, roe deer, aurochs, elk, and hog, and edible plants such as hazelnuts, black berries, crab apples, plums, and pears (Barker 2006, 332–333). This environment, which was the habitat of European Pleistocene foragers, was also the foundation for the swift spread of agriculture, which continued to use hunting and fishing as a subsistence alternative (6.4). Agriculture in Central-Northern-Eastern Europe spread swiftly with the appearance of Early Neolithic Linearbandkeramic (LBK) pottery around 7,500 BP, stretching from Central Europe to the Baltic and from the Paris basin to the Carpathians. The LBK culture remained stable for about a millennium, and marked the northern frontier of agriculture. Gradually, agriculture was implemented northwards, likely through trade and acculturation (Barker 2006, 357–364). Accordingly, agriculture played an immense role in subsistence in most prehistoric and historic populations of our area, and agriculture constituted a fundament of most cultural systems. Even though hunting and pastoralism did exist in parallel (6.4.2, 6.5.6), and were continuously used as a complement, crop failure had a huge impact on the population, leading to starvation, sickness, and death of the livestock. Agriculture also involved the development of a number of practices, both concrete and more abstract, and both direct and indirect; which were partly local, depending on the environmental circumstances, and partly similar over the entire area. An important foundation for agriculture were practices of land use, i.e., the utilization of the land and its resources without impoverishing the soil, typically manifested through practices of distribu-

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tion of pasture and tilled land, crop rotation, and reuse of the livestock for pasture and fertilization. Another concrete result was the emergence of specific tools and artifacts, used for tillage and the preparation of secondary products (6.6.3). A further cultural outcome of cultivation was the development of calendric systems, naming the seasons, and even the months and weekdays, which developed in parallel, sharing many substantial similarities over the entire area (6.12.1). In general, a fundamental cultural difference between foragers and farmers is manifested through the mythic systems, the societal structure, as well as the relation to the environment. Foragers have a mythical relation to the environment, and articulate nature as “kin”, whereas farming societies (e.g., as observed on non-Western farming societies) are commonly characterized by cults of fertility and involvement of calendric rituals; reproduction of the social group is central, and ancestors and kinship are perceived as ideology (Barker 2006, 409). This is a pattern that is prevalent also in most of our ancient societies: the entire process of cultivation, its connection to the seasons, the calendric system, the earth, as well as the procedures and implements used for cultivation, all play a central role in most ancient beliefs. Feasts and festivities, in ancient times as well as later, are closely connected to the procedure of cultivation, such as plowing, fertilizing, sowing, slaughtering, and harvesting. Cultic activities were obviously present already in the earliest Neolithic communities, marking a distinct difference from earlier huntergatherer populations (Dietrich et al. 2012, Hodder 2010). In farming mythologies, gods and goddesses of cultivation and earth are also fertility deities, connected to well-being, thriving, reproduction, and kin, but sometimes also conversely to death. The most prototypical example of this mythological complex is the goddess Demeter in GrecoRoman mythology, who personifies all these functions in one conglomerate of deities: she is the goddess of the earth, of the underground (through her relation to Hades), but also of agriculture, land cultivation, family, and reproduction, and, through her daughter Persephone, to the seasonal changes (Pauly 1901, 2713–2764). Another example is the complex of the siblings Frey and Freya in Germanic mythology, gods of fertility, prosperity, peace, and agriculture (Andersson and Granlund 1959, 616–620, Puhvel 1987, 205–210), a connection appearing also in the Celtic horse goddess Epona, who symbolizes fertility, the abundance of the earth, kin (through her role as mother goddess), healing, as well as death (Green 1992, 90–92). The following chapters will deal with various aspects of agriculture, as they are manifested in language through cognacy, borrowing, colexification and meaning change. We will focus on the following areas: land use, aiming at the impact on the land by agriculture; tillage, including instruments and implements used for farming; cereal agriculture, including ancient species of cereal used in agriculture; vegetables and arboriculture; and finally textile agriculture.

6.6.2 Land use Activities of agriculture, compared to hunting and gathering (as well as pastoralism), leave considerable marks on the land, which are often persistent and can be identified by archaeological excavation. Therefore, we are relatively well informed on the practices of land use by prehistoric farmers. Agricultural subsistence typically involves archeological remains in the form of settlements, including buildings for kin, livestock, and crop (sometimes separated). These are surrounded by fields, which are often systems, enclosed by ditches, walls, terraces, or similar. These settlements leave a large amount of traces, in the form of pollen, plant material, dung, organic material, animal bones, and human remnants (Barker 2006, 76–96). Our chapter “land use” includes the concepts cultivated field and furrow. In our classification, we group these two concepts together with plow (n), due to their behavior in terms of borrowability, semantic instability and cognacy, which differs from other tools and implements, which we treat under a class implements (see 6.6.3). In our data, cultivated field and furrow form a cluster in terms of colexification and meaning change (fig. 28). As we have seen before, the chart informs us about other concepts that

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Figure 28a: Colexification and meaning change for cultivated field and furrow (Indo-European).

Figure 28b: Colexification and meaning change for cultivated field and furrow (Caucasian).

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also should have been included. The network based on only these two concepts give the following main nodes: field, with the extra nodes plain, ground, village, pasture. Furrow yields the further nodes groove, channel, trench, ditch. The network created by cultivated field and furrow is huge, but not particularly interesting in terms of metaphorical changes, which are very few (e.g., palm, hair). Most changes are either specializations or metonymic meaning changes, staying within the semantic area of land use, basically targeting the land and occasionally the activity of using the land (e.g., to plow, spade).

6.6.3 Tillage Specific subsistence activities are connected to the use of specific artifacts; tools prototypical for farming include axes, adzes, mattocks, hoes, spades, baskets, and sickles. A general problem of the reconstruction of these tools and their usages is the fact that several of them were completely or partly manufactured in wood, which is not preserved (6.9.1). However, there are several alternative ways of reconstructing the use of these tools in archaeological research, such as to consider marks and traces, or “damage signatures”, in more persistent materials (Barker 2006, 76). A specifically important development in the pre-history of the area was the invention of the plow, originally a technological improvement or a mechanization of a hand-held hoe, using the large domestic stock for pulling. This development, belonging to the Secondary Products Revolution in the Early Chalcolithic, greatly increased the efficiency of agricultural practice (Greenfield 2010). The earliest evidence for plows are from the Near East, around 7,000 BP, representing basically two-handled plows with a composite draft pole, whereas the earliest European plows are single-handed plows, or ards (Mallory and Adams 1997, 435). In the farming procedure, tools such as spades, hoes, and plows are used in the preparatory phase, where the soil is prepared for sowing by destroying weeds. The next phase involves the sowing of the seed, and when the time is ripe for harvesting, other implements are involved, depending on the type of crop. For cereals, the main tools for harvesting include knifes and sickles. The earliest sickles are from Southwest Asia and Egypt, from ≈ 10,000 BP, and were made from a series of stone blades inserted into a wood handle. The sickle in the archaeological record continuously follows the Neolithic agricultural revolution to Europe, West, and South Asia. Sickles made from metal constituted a great improvement to this instrument, an innovation that coincided with the Chalcolithic Revolution 6–5,000 BP in the Near East, Southern Caucasus, and Central Europe (Mallory and Adams 1997, 517). The form of the sickle, a curved metal knife with a wooden handle, remained consistent, with slight local deviations, until present day. A later development of the sickle was the scythe, which developed during the Iron Age as a more ergonomic improvement. Even after the introduction of the scythe, the sickle remained the main instruments for harvesting cereals (Andersson and Granlund 1965, 539–542). There are overlappings, as well as differences, in the behavior of lexemes for land use and tillage, which have influenced our dealing with these concepts as well as our classifications. Lexical concepts of our corpus include plow, scythe, sickle, spade, axe, and saw, and the activities to plow, and to sow. In our original plan, we aimed at including tillage implements here and deal with tools mainly used for lumbering and woodworking (e.g., saw, axe) separately (see 6.9.1). However, in terms of colexification and meaning changes, all tillage tools turned out to be completely integrated, and we therefore decided to treat them together. The concept knife we classify as an implement, but in terms of colexification, we deal with knife under Weapons and warfare (6.10). The implements of tillage and weapons are highly integrated and difficult to distinguish and classify. In Indo-European, we may reconstruct roots for the verb to plow (PIE *h₂erh₃- ‘to plow’) as well as the instrument of plowing, plow (n) (PIE *h₂erh₃-tro- ‘plow’). Lexical substitution and parallel roots occur in sub-branch proto-languages (see appendix 3b). In Caucasian languages, there are several alternative roots, leading to ‘plow’ as well as adjacent implements and ‘plow-

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Figure 29a: Colexification and meaning change for IMPLEMENTS and PLOW (N) (Indo-European).

share’ (PKv *ečʰw- ‘adze’, PNWC *ćwa ‘plowshare’, PN *astʰ-in, *astʰ-en ‘hoe; small adze; endscraper; wooden tool’, PD *wecʰ:- ‘wooden plow’; PKv *ɣinc’w-, *ɣinc’-a ‘plow (wooden); plow knife’, PNWC *ɣənc’-ă, *ɣancʰ-ă ‘wooden plow; hook’, PN *ɣac’ ‘to scratch’, PD *ɣanc’-a ‘hook; plow’; PKv *barcʰx-, *pʰarcʰx- ‘rake’, PNWC *bəʒ’-a, *pʰəʒ’-a ‘plowshare’, PD *barcʰ:-, *pʰarcʰ:‘wooden plow; plowshare’; PKv *erkʰw-an- ‘plow handle’, PD *ħare- ‘to plow’). The Uralic words are loans from Indo-European, alternatively Germanic, or derived from a root ‘to dig’ (appendix 3b). As for the other implements, there are several tools that can be reconstructed, as well as parallel tracks of innovations, which are highly interesting (see appendix 3b). Both tillage and implements are high in semantic instability and cognacy (fig. 30a, 30b). The network of colexification and meaning change of implements and plow (n) (fig. 29) is the most complex in our collection (we have excluded the verbs here). It is noteworthy in terms of its enormous richness and complexity, but it is not particularly surprising in terms of metaphoric or even metonymic changes. As expected, we find nodes of concepts which we should have included from the beginning, including, e.g., shovel, hoe, oar, mattock, rake, stake, adze, hatchet, hook, sword, club, pole, pin, dagger, clasp, brooch, nail, needle. An interesting metonymic group includes channel, furrow, ditch. Besides, we find a huge number of specializations of various tools and implements, as well as, the expected derived verbs.

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Figure 29b: Colexification and meaning change for IMPLEMENTS and PLOW (N) (Caucasian).

Figure 30a: Borrowability (x), semantic instability (y) and cognacy (node size) for TILLAGE.

Figure 30b: Borrowability (x), semantic instability (y) and cognacy (node size) for IMPLEMENTS.

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Map 38a: Cognacy map for the concept plow (n) (modern languages).

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Map 38b: Cognacy map for the concept plow (n) (ancient languages).

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6.6.4 Cereal agriculture The domestication of wild cereals was an achievement of the initial Neolithic revolution that was contemporary with, or maybe even predated, the domestication of livestock (Willcox, Buxó, and Linda 2009). The earliest domesticated cereals, including wheat species, basically einkorn (Triticum monococcum) and emmer (Triticum turgidum); barley species, basically two-rowed barley (Hordeum distichum), modified to six-rowed barley (Hordeum hexastichum), and hulless barley (Hordeum vulgare), and rye (Secale cereale); all have wild progenitors, which are natural in Southwest Asia and Central Europe, including wild einkorn (Tritum boeoticum), wild barley (tworowed barley, Hordeum spontaneum), wild emmer (Triticum dicoccoides), and wild rye (Secale montanum) (Barker 2006, 104–109, Willcox 2005, Willcox, Buxó, and Linda 2009). The domestication occurred within the area of the initial Neolithic revolution, but it is likely that the process was a parallel evolution, emerging at multiple centers rather than from a core area (Willcox 2005, Fuller, Willcox, and Allaby 2011, Willcox, Buxó, and Linda 2009). Wheat and barley species were the most frequently cultivated cereals, whereas rye occurred more sparsely in early Neolithic sites in in Anatolia as well as in Europe. It is possible that rye was a weed, accompanying wheat and barley, rather than a cereal domesticated for its own purpose (Mallory and Adams 1997, 491). Subsequently, the domestication of these grains continued to spread with agriculture to the west, east, and north. In this procedure, the cereals had to meet with changing climate circumstances, to the north and northwest by an increasing cold-temperate climate, and to the east and southeast a steadily increasing rainfall (6.6.1). Moving eastwards, the cultivation of cereals, particularly wheat, was gradually replaced by the cultivation of rice. In Northern Europe, the earliest Neolithic cereals, including emmer, einkorn, and barley, were still in use during the Viking age but were successively replaced by rye, a cereal that was better suited for a colder climate, as well as by oats. The cereal oats is somewhat obscure in its origin, but it is likely that oats emerged as a weed admixture in emmer and einkorn in Neolithic Anatolia, and then subsequently replaced these cereals, as cultivation moved northwards. Like rye, oats turned out to be better adapted to a cold climate than wheat and barley (Andersson and Granlund 1962, 172–175, 1961, 67–70, Kulp and Ponte 2000, 171). Due to their inherent characteristics, the cereals have different functions, which have changed over time. The most important distinction was whether they were used mainly for human or animal consumption, and whether they were used for baking bread or for soup, porridge or drink. The hardiness of the cereals also had an impact on their use, in particular in coldtemperate climates. Wheat was generally the most highly valued grain for baking bread and remained the most important cereal, in areas with a favorable climate, such as the Mediterranean, Southwest and Southeast Asia. In cold-temperate climates, particularly in Northern Europe, wheat was successively replaced by hardier cereals, including barley, rye, and oats during the Bronze Age and the Iron Age. However, at least emmer continued to be in use up to the Viking Age. Barley is hardier than wheat but is not very useful for baking porous bread, instead, its main use included porridge, flatbread and fermented drinks, such as beer. Human consumption typically involved the hulless barley, which has the characteristic of having an easy-to-remove hull, which falls apart during threshing. The other barley species were also important as animal fodder. In the ancient Mediterranean, oats were used as animal fodder, and this was the main use of oats in Northern Europe, even though the use in Middle ages was extended to porridge and soup. Therefore, rye remained the most important cereal for bread in northern, cold-temperate climates, such as Northern Europe. Here, grains were not seldom mixed in bread (Andersson and Granlund 1972, 659–663, 1961, 267–269, 1962, 172–174, Kulp and Ponte 2000, 81 ff., Andersson and Granlund 1957, 405–407, 1969, 551–558, Mallory and Adams 1997, 51–52, 409, 491–492, 639– 641). We can reconstruct a number of specific domesticated cereals to Proto-Indo-European (Blažek 2017, 163–167, Mallory and Adams 2006), indicating that the Indo-Europeans were well acquainted with cereal agriculture (PIE *bheuh₂-u- ‘barley’ < PIE *bheuh₂- ‘to grow, be’; PIE *ghr̥-

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Figure 31: Borrowability (x), semantic instability (y) and cognacy (node size) for CROPS.

yo- ‘barley’; PIE *yewh₁o- ‘barley’; PIE *sh₁(e)s-yo- ‘grain, corn’; PIE *(H)meyǵ(h)- ‘barley, corn’; PIE *h₂elbhi- ‘barley’; PIE *ǵrh₂-no- ‘grain’; PIE *h₂edos- ‘sort of cereal, grain’; PIE *dhoH-neh₂‘grain, bread’; PIE *proḱso- ‘grain, millet’; PIE *pHu-ro- ‘corn, wheat’). This is also the case with Caucasian families, with several intertwined etymologies also leading to other crops (PKv *č’waw- ‘rye’, PD *č’war- ‘rye’; PKv *maxa ‘type of wheat; barley’, PNWC *mxă ‘cornfield; crops’, PD *maqw-a ‘barley’, PN *maq-i ‘barley; bread’; PKv *kʰrtʰ-il ‘autumn barley’, PNWC *kʰatʰ-i ‘grain; barley’, PD *kʰwed-o ‘oats’, PN *kʰotʰe ‘barley’; PKv *bačʰ-a ‘millet; pea’, PNWC *mačʰʲ-ă ‘pea; bread’, PD *bačʰwa ‘pea’, PN *borcʰ- ‘pea’; PKv *lark’ ‘seed’, PNWC *k’a ‘seed, fruit stone’, PD *lak’-a ‘grain’, PN *lak’ ‘fruit kernel’; PKv *kʰob- ‘rye’, PNWC *bagʲə- ‘oats’, PD *o-gob- ‘rye’; PKv *k’il- ‘pericarp, husk’, PNWC *k’ʲəw- ‘grain; stone’, PD *nak’- ‘wheat’, PN *k’aw- ‘wheat, wheat grain’; PKv *dik’-a ‘wheat’, PN *dik’wa ‘rice’, PD *dik’w-e ‘millet’; PKv *qwarb-al- ‘wheat’, PD *qa:b-o ‘bread’, PN *qa:b- ‘to feed’). In our Uralic data, all grain words are loans from Indo-European (occasionally from Hungarian). The colexification and meaning change network surrounding grain and the various species of grain (fig. 32), including barley, wheat, oats, rye, is extremely rich and complex, and contains a large amount of specializations and metonymic and metaphoric changes, referring to various characteristics of grain and species of grain. A central group of nodes informs us about additional concepts that belong into the semantic sphere of the grains, including bread, food, corn, cereal, kernel, crop, seed, particle, semen, grape, berry, flour, emmer. A further group includes harvest, but also money, profit, interest, goods, wares. The group containing page, sheet, blade, leaf, tongue refers to the flatness of grain, whereas the other meanings refer to the ripening, by the verbs to grow old, to age, to wear out. Another group refers to the smallness of grain, by gravel, stones, earth, grit, sand, rubble. The group crops is also have high rates in semantic instability (fig. 31).

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Figure 32a: Colexification and meaning change for CROPS (Indo-European).

Figure 32b: Colexification and meaning change for CROPS (Caucasian).

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Map 39a: Cognacy map for the concept grain (modern languages).

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Map 39b: Cognacy map for the concept grain (ancient languages).

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Map 40a: Cognacy map for the concept wheat (modern languages).

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Map 40b: Cognacy map for the concept wheat (ancient languages).

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Map 41a: Cognacy map for the concept barley (modern languages).

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Map 41b: Cognacy map for the concept barley (ancient languages).

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6.6.5 Vegetables and arboriculture The issue of horticulture versus agriculture – garden cultivation versus field cultivation – is a matter of discussion among archaeologists and paleobotanists. Horticulture or gardening refers to small-scale cultivation of food plants in gardens, while agriculture refers to more large-scale cultivation of fields. This is a valid opposition in some environments, whereas there is, in other environments, no reason to make a distinction between these two systems. More important for ancient farming is to define the context, nature, and scale of agriculture. e.g., intensity and scale of cultivation, range and type of plant species, or forms of cultivation. An important distinction is the difference of intensive and extensive systems, a metric which measures input and return per unit area, compared to return per capita (Van der Veen 2005). Under the heading of vegetables and arboriculture, we will look at three crops which were of importance in many cultures of our area, but which do not belong to the initial Neolithic farming revolution, namely grape, apple, and turnip. Grape and apple grow wild in distinct areas and it may be difficult to distinguish domesticated from wild forms in the archeological track record. Apple grows wild in temperate zones, with four main species, Malus sylvestris, Malus orientalis, Malus baccata, and Malus sieversii, and it is evident that the wild apple was an important part of the diet of Neolithic farmers as well as Bronze Age populations in the Near East and the Mediterranean, and was also used for producing fermented drinks, such as wine (6.7.2). However, the domesticated apple (Malus pumila, Malus domesticus) has a history that begins in Central Asia during the Bronze Age, from where it spread westwards along the Silk Road, probably carried by horse caravans. Evidence of the domesticated apple in the area of Europe-Near East is attested from Israel by 3,000 BP (Cornille et al. 2014, Harris, Robinson, and Juniper 2002). As far as mythology is concerned, it is worth mentioning that the apple plays a role in several cultures, typically in the function of “golden apples”, which are highly desired, divine fruits, a source of eternal youth or immortality, and which are stolen or in other ways a source of discord (e.g., Baltic, Germanic, Slavic, Greco-Roman mythology) (Gamkrelidze, Ivanov, and Winter 1995, 553–554). Grape domestication is dealt with under 6.7.2, which describes the emergence of wine and viticulture. The history of the domesticated turnip (Brassica rapa) is obscure, but we know that it was a planted vegetable at least in the ancient Mediterranean. Wild turnip is distributed over Europe and and genetic studies indicate that domestic species of turnip have a wide range of genetic variation, but that the domestication was made directly from wild species in Europe and the Near East, but that a continued cross-breeding with wild species occurred (Bell 2006, Guo et al. 2014). The root for apple can safely be reconstructed to Proto-Indo-European (PIE *h₂eb-ōl‘apple’), as well as Caucasian (PKv *mažal- ‘apple’, PNWC *maźwă ‘apple’; PKv *wašal- ‘apple’, PD *ωešn- ‘apple’). The Proto-Finnic term is an Indo-Iranian loan (PFi *omena, *omɜrɜ ‘apple’). Roots for grape in Indo-European are more complex, with lots of parallel tracks. Besides the widespread root for ‘wine’, common to Semitic, Caucasian and Indo-European, for which the ultimate origin remains obscure, we cannot reconstruct a single Indo-European root with the meaning ‘grape’. The Caucasian root is also unclear in its meaning (PKv *xixw- ‘species of white grape’, PD *qixw ‘hazelnut’). Likewise with turnip, for which no specific reconstructed root is possible, neither in Indo-European nor in Caucasian (see appendix 3b). In colexification and meaning change, turnip does not give particularly wide and interesting connotations, basically it stays below the earth (root, beet), where it also may change size and species (rapeseed), or stay close to the ground (cabbage), occasionally with a metonymic change to the plant of other species (rape plant, wolfsbane). Apple and grape, though, cluster together and demonstrate interesting connotations (fig. 34). Besides various specializations and changes to other species (pear, potato, rowanberry), we find interesting metonymic and metaphoric changes, which unite apple and grape. One group involves a metaphoric change to things with a graspable form, e.g., clamp, door-handle,

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Figure 33: Borrowability (x), semantic instability (y) and cognacy (node size) for VEGETABLES AND FRUIT.

hook, claw, or items that imply a mass, i.e., cluster (basically grape). Another group of words metonymically target parts of the horticulture settlement as well as beyond, e.g., settlement, garden, thicket, forest, or the entire plant, e.g., fruit tree, willow. Metaphoric changes imply youth and beauty, e.g., young man or beautiful woman. On averge, vegetables and fruit have medium or low rates of borrowability or semantic instability (fig. 33).

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Figure 34a: Colexification and meaning change for APPLE and GRAPE (IndoEuropean).

Figure 34b: Colexification and meaning change for APPLE and GRAPE (Caucasian).

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Map 42a: Cognacy map for the concept apple (modern languages).

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Map 42b: Cognacy map for the concept apple (ancient languages).

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6.6.6 Textile agriculture In our area, there are two important crops domesticated for the purpose of textile production, flax (Linum usitatissimum) and hemp (Cannabis sativa). Besides wool, flax remained the most important material for textile production, predating wool in emergence, which was introduced first by the Secondary Products Revolution in the Chalcolithic period (Greenfield 2010) (6.5.9). The domestication of flax developed in the early Neolithic period (10,500–9,000 BP) in the Northern Levant, by the wild progenitor Linum bienne, which occurs as a perennial in Mediterranean and Atlantic coastal areas, and as a winter annual in Iran and Iraq-Kurdistan (Barber 1991, 11). The domestication of flax was simultaneous with the domestication of sheep, pig, and cattle (Zeder 2008). After the initial domestication, flax spread successively towards the East and West by the Neolithic revolution and is attested in sites across Europe and in Ireland at the beginning of the Bronze Age (4,200 BP) (Mallory and Adams 1997, 206). Flax remained important as a material, cultivated for textile production up to the modern era. Flax produces a stable and soft fiber, known as bast, which is highly functional for spinning and weaving for cloth production. The extraction of the bast from the plant follows a specific procedure, which has not changed much over time. Because younger plants produced softer fiber, cultures had to choose between harvesting the young plant for its soft fiber, or waiting until the plant produced seeds, used for oil, and obtaining coarser fibers. First, the young plant is pulled by its roots. In a second step, the plants are dried and put in a place to rot away the material that surrounds the bast, a procedure known as retting. Thereupon, the flax is dried again, and the remaining stem material is removed by breaking, scotching and finally by heckling, a process that involves specific tools, which are found in archaeological data (Barber 1991, 11–15). Hemp is another bast fiber plant of importance to textile and rope production. The plant hemp (Cannabis sativa) is considerably taller than flax (up to 4–5 meters), and found in its wild state in Central Asia. Hemp produces bast, which is similar to flax fiber, but it is longer, coarser, and therefore useful for coarser textile production, such as ropes and sails. For flax, a common root in Indo-European can be reconstructed to the proto-language (PIE *līno-, lino- ‘flax’), even though some consider the word to be a substrate or migration term. In Caucasian, we have a parallel root, but the meaning ‘flax’ can only be safely reconstructed to Proto-Kartvelian (PKv *sel- ‘flax’, PNWC *pʰšə ‘corn; millet’, PD *swa- ‘small chaff; millet’, PN *swa- ‘barley’). Most Uralic terms are loans from Indo-European (appendix 3b). In colexification and meaning change, besides specializations of parts of the plant (flax seed, flax plant) or generalizations (e.g., fiber, stem), flax changes stay almost entirely within the area of clothing. We have, e.g., linen, garment, thread, handkerchief, napkin, shirt or to card, to comb (appendix 3b).

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Map 43a: Cognacy map for the concept flax (modern languages).

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Map 43b: Cognacy map for the concept flax (ancient languages).

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6.7 Food preparation 6.7.1 Food preservation An essential ingredient for food preservation is salt, which was extracted by Neolithic farmers already around 7,500 BP. Salt also has the function of being a vital ingredient in the human diet. Since salt is a non-permanent material, which becomes dissolute, and is hard to track in the archaeological record, various evidence has to be used for tracing the Neolithic extraction of salt. Likely, salt was extracted from either water, soil, rocks, or plants, such as by salt springs, excavated and supported by wooden structures for the purpose of extracting salt (Central Europe, 7,600 BP) (Weller 2015). Salt is, in terms of borrowability, sematic instability, and cognacy a very stable term, and is therefore classified among the products. In Indo-European, one single root dominates almost the entire map (PIE *seh₂l- ‘salt’), a root that is also loaned into Uralic languages. The concept can also be reconstructed to Caucasian (PKv *ʒam- ‘vinegar; salt’, PD *ʒan- ‘salt’). In meaning change, salt (appendix 3b) has relatively few semantic changes, mainly to sea, salt water, but also occasionally to, e.g., pepper and bacon.

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Map 44a: Cognacy map for the concept salt (modern languages).

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Map 44b: Cognacy map for the concept salt (ancient languages).

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6.7.2 Drink and drugs Over time and considering our large area, a significant number of natural substances, e.g., plants or mushrooms, must have been used for the purpose of intoxication. However, a couple of important substances can be highlighted here, which are also related to the emergence of agricultural practices, and which had a prominent position in feasting and cult practices. The first is beer, a fermented drink based on cereals (emmer, einkorn, barley), the production of which involves mashing, malting, and brewing, which can, using various evidence, be traced in the archaeological record. Beer production can be traced to the earliest Neolithic farming societies, with evidence, e.g., from Anatolian cultic site of Göbekli Tepe (PPNA, 11,500–10,000 BP) (Dietrich et al. 2012). Accordingly, the process of beer brewing continued through the Neolithic and Chalcolithic, and is found in the early track record from the Near East, Mesopotamia, Egypt, and Europe (Dineley 2004). The other important fermented drink is wine, which is somewhat different from beer, since it is produced from grapes, which cannot be grown in colder climate zones. The domestic grape vine (Vitis vinifera) was originally derived from the wild vine (Vitis vinifera vs. sylvestiris), which is, though the grapes are somewhat smaller, also fully capable of producing fermented wine. Wild vine occurs throughout the Mediterranean, in Anatolia, the Caucasus and beyond the Caspian sea, and in Northern Ukraine (Mallory and Adams 1997, 664). The earliest evidence of grape fermentation and viticulture, mainly based on chemical analyses of organic compounds absorbed into pottery, point to the southern Caucasus 8,000–7,800 BP (McGovern et al. 2017) and it is also around this period that Vitis vinifera sylvestris was domesticated in the southern Caucasus and Anatolia (Estreicher 2017). Another important fermented drink is mead, which is produced from honey. Mead production is connected to the production and consumption of honey and the domestication of bees (6.5.3). A further substance of importance is cannabis, which was cultivated for making ropes as well as for intoxication (6.6.6). The issue of drink and drugs encompasses the culture of intoxication, feasting, cult practices, and libation, which are important in several ancient cultures of our area. In particular, the importance of fermented drinks can be concluded through their prominent role in mythology. In the Greco-Roman as well as in the Celtic pantheon, the substance wine (often together with bread) or a wine-vessel are attributes of several gods and goddesses, such as the Greek deity Dionysos, the Celtic Hammer-god, or the deity Rosmerta, symbolizing prosperity as well as blood (Pauly 1903, 882–1046, Green 1992, 227). The toxic drink mead plays a prominent role in many IndoEuropean cultures and religions, and mead as a sacred drink is paralleled by the story of Kväser in Germanic myth, where mead is a source for inspiration for poetry and wisdom, and mada- in Indo-Aryan myth as a source of toxic madness, through the monster Mada (Puhvel 1987, 210–211, Glasenapp and Carlstedt 1976, 166). Unfortunately, our corpus does not include beer, but the Indo-European reconstructed form (PIE *h₂el-u- ‘beer’) reoccurs in several other toxic drink words, such as mead. For mead, we may reconstruct an Indo-European root, typically intertwined with honey lexemes (PIE *médhu‘honey, mead’). The words for wine are very stable and the root shared between Indo-European, Caucasian, and Semitic proto-languages dominates the map (PIE *uoh₁i-no- ‘wine’ < PIE *ueh₁-i- ‘to turn, wind’; PKv *ɣwin- ‘wine’, PNWC *ωwə- ‘wine; alcoholic drink’, PD *ωun- ‘wine; one-year-old vine shoot’). The Uralic forms are borrowed from Indo-European (see appendix 3b). In terms of stability, mead and wine are different (fig. 35). In colexification and meaning change, the alcoholic beverages cluster together, also including honey (fig. 36). As mentioned before, we did not include beer, but the meaning change chart corrects this mistake, putting beer (and ale) as an important node in the center of the chart. A few semantic domains may be mentioned, e.g., reference to fluidness (juice, nectar) or sweetness (delight, sweet talk, sweetness). The concept wine has surprisingly few connections. However, the chart is surprisingly modest, compared to, e.g., apple and grape (cf. also milk, fig. 24).

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Figure 35: Borrowability (x), semantic instability (y) and cognacy (node size) for DRINK AND DRUGS.

Figure 36a: Colexification and meaning change for WINE, MEAD and HONEY (Indo-European).

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Figure 36b: Colexification and meaning change for WINE, MEAD and HONEY (Caucasian).

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Map 45a: Cognacy map for the concept wine (modern languages).

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Map 45b: Cognacy map for the concept wine (ancient languages).

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6.7.3 Agriculture (food and clothing) products and activities – an overview Products of agriculture and hunting, which are used for preparing food or clothes, including honey, hops, milk, salt, wax, wool, and meat, have been dealt with under the various domains of agriculture that produce them (for salt, see 6.7.1). Their colexification networks are also somewhat different, but they do not, with a couple of exceptions, cluster with their sources, i.e., the animals or implements that produce them. However, in terms of their behavior in borrowability, semantic stability, and cognacy, there are pronounced differences, both between food products as well as in relation to their origins (e.g., cow for milk, bee for honey). This has forced us to introduce a distinction between products aiming at the production of food and clothes (labelled products, fig. 37), products which are a result of a fermenting process (drink and drugs, fig. 35), and products that belong to the sphere of hunting, skin and fur production, and woodworking (materials, 39). The motivation is mainly their behavior in terms of stability. The food and clothing products are highly stable, the drink and drugs are more unstable, and the hunting and woodworking materials highly unstable. A glaring exception is the words for the

Figure 37: Borrowability (x), semantic instability (y) and cognacy (node size) for PRODUCTS.

Figure 39: Borrowability (x), semantic instability (y) and cognacy (node size) for MATERIALS.

Figure 38: Borrowability (x), semantic instability (y) and cognacy (node size) for ACTIVITIES.

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trees (birch, elm, beech), which are among the most stable in our data. For an overview of the classification, see table 35. Another issue is activities, i.e., the verbs for the activities that relate to artifacts and products in our data. These are to plow, to sew, to sow, to spin (thread), and to weave. Probably due at least in part to being verbs, these concepts are all very stable, something that has made it necessary to treat them as a separate group (fig. 38).

6.8 Leather, textiles, and fabric 6.8.1 Skin and fur production In particular, the Northern areas of Europe and Asia were rich in animals, such as bear, wolf, fox, otter, and marten, whose fur was used for clothing. These animals also were an attractive hunting game (cf. 6.4.1–2). The use of animals’ hide for clothes in colder climate dates back to Paleolithic times and was used by, e.g., the Neanderthals in Europe and Asia. In antiquity, in particular among Germanic and Celtic tribes, but also Thracians, Gets, and Scythians, fur was frequently used for clothing. Among Greeks and Romans, fur clothing, e.g., of lions, bears, aurochs and other game animals, had a mythical and ceremonial function, to symbolize victory and dominion over dangerous animals (cf. 6.4.1–3). Fur of predators gradually became a luxury in the Mediterranean area, which led to an increasing trade from Northern parts of Europe to the Mediterranean, as well as a source of loans of words for various fur species. Fur even became a means of payment (Schrader 1929, 156–159). Both fur and leather are extremely complex. In Proto-Indo-European, there are two roots with the meaning ‘skin, hide’ (PIE *(s)keh₁u-ti- ‘skin’; PIE *pel-ni- ‘skin, hide’), which are the ultimate root of many fur and leather words. However, in branches and languages there are many parallel tracks and a lot of lexical substitution and meaning change (see appendix 3b). We find the same pattern in Caucasian (appendix 3b). The extreme complexity of fur and leatherwords is reflected in the high semantic instability scores of these words (fig. 35). In colexification and meaning change charts (fig. 40), we have grouped fur, leather, and wool into one chart, which is very rich and complex, mainly due to fur and to leather (see before). At the center of the network, we have nodes such as skin, fleece, hide, animal skin, hair, membrane, sheath, film. Another cluster relates metonymically to the animal origin, e.g., fodder, food, to activities of preparing, i.e., to comb, to card, to shear, to pluck, to skin, to flay, or the products, e.g., pelt, whip, lash, bag, pouch. The use of fur for clothing is evident through garment, gown, dress, coat, tunic (cf. 6.6.6, linen). However, the high value of fur as a means of payment is not reflected in our corpus.

6.8.2 Textile production The technology of twisting threads for sewing is very old and is found already in Gravettian (Europe, 33–22,000 BP) and Magdalenian (Central Europe, 17–12,000 BP) cultures. A solution used all over the world for this purpose is to make use of a stick and a rock, typically a disc with a hole, combined to a spindle whorl, with a double use: it helps spinning the thread and functions as a package for unraveling the spun thread. This device is found in many forms and variants, from preforms to full spindle whorls, in archaeological data over our entire area. Even though there are, e.g., in Ancient Egypt, examples of more mechanized variants of spinning, the spindle whorl technology remains remarkably consistent. In general, spinning methods/materials of our area fall under three main types, found in the areas of Egypt (high whorl spindle, S-spun linen thread), Egypt/Anatolia (low whorl spindle, Z-spun wool and linen), and the Middle East (high whorl spindle) (Barber 1991, 42–78).

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Figure 40a: Colexification and meaning change for FUR, LEATHER and WOOL (Indo-European).

Figure 40b: Colexification and meaning change for FUR, LEATHER and WOOL (Caucasian).

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The main technology in prehistorical and historical times for preparing cloth, is weaving. The process of intertwining or braiding natural material for adornment or for clothing purposes, e.g., making hats against the sun or wind, belts for keeping up fur skins, or to create simple shoes, has a long history, dating back to the Upper Paleolithic. By definition (Barber 1991, 79 ff.), weaving involves the practice of using two elements, a fixed set of threads or other material, the warp, and a second set of elements, the weft, which is intertwined with the first set. The main difference to basket making or other types of plaiting or braiding, is the use of a fixed warp and a longer and more flexible material as weft. A precondition of the process is thus some sort of preparation of the interwoven material, to make it flexible and adaptable to the warp. Another ancient technology used for preparing cloth out of wool and hair is known as felting, where a stable, thick fabric is prepared by a combination of pressure, warmth, and dampness. Felting was spread all over Europe and Asia already in ancient times and remained important in selected parts, but was ousted by weaving in the south (India and Middle East), and the West (Europe) (Barber 1991, 215). In our corpus, we have decided to treat the textile production words through verbs (cf. Tillage 6.6.3), which affects the outcome in stability and borrowability (see appendix 3b for reconstructions and 38 for scores).

6.9 Processing of basic materials 6.9.1 Trees, lumbering and woodworking Wood as a material was fundamental to all cultures of our area. Wood was a prerequisite for maintaining the fire, a necessity in colder climate zones, but also an important source for food preparation. Further, wood was central, already in the Neolithic, in the construction of dwellings for family and livestock and for walls and enclosures, protecting against predators as well as enemies. Another important area of usage for wood is artifacts, from plows, sticks, spades, and other digging tools, to furniture, such as tables and chairs, and various implements, such as vessels, spindles, or handles. During the Neolithic period, wood was typically used in combination with stone to construct tools and weapons, but even after the Secondary Products Revolution and the Chalcolithic development of metallurgy (6.9.2), wood continued to play an important role: metal was precious and heavy, and a typical tool or weapon was mainly made of wood and only its vital part, e.g., the tip of a plow, arrow, or spear, was metal. Even though wood is an impermanent material, which decomposes over time, we are relatively knowledgeable about the distribution of prehistoric use of various wood types. Prehistoric pollen can give us information about the spread of tree species, which together with their inherent qualities and usage areas historically enables us to reconstruct the prehistory of various tree types. During the Boreal period (7,000–5,000 BP), rich amounts of pollen were spread over the area, from the Atlantic to India to the Urals and to Central and South Asia, yielding enormous and rich forests, of which the forestation was vital to human settlement (Mallory and Adams 1997, 599–601). Our area spans several climate zones: boreal Northern and Eastern Europe, warm temperate Central and Southern Europe, partly boreal, arid, or warm temperate Central and Western Asia, and equatorial and summer-dry Southern Asia. Thus, the area is home to a diverse range of tree species. Important trees within the core area of the Neolithic revolution (Europe, Mediterranean, and Northeast Asia), both in present and prehistory, include alder, apple, ash, aspen, beech, birch, cherry, elm, fir, hawthorn, hazel, hornbeam, juniper, linden, maple, mulberry, nut, oak, pine, sloetree, willow, and yew. These trees are found in most ancient Indo-European languages, and are predominantly warm temperate climate trees (Mallory and Adams 1997, 599–601, Cabi 2013). In a northern, boreal climate, most of these trees do not survive, and we find other forest types, typically conifer trees, such as different species of spruce, which also grows in Central European mountainous areas (Cabi 2013, 318), or specific species of pine, such as the Siberian stone pine (Cabi

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2013, 367). A few species, such as the common aspen, are both boreal and warm temperate trees (Cabi 2013, 393). Arid and warm temperate zones with hot and dry summers, typically including Southern Europe, Northern Africa, and West Asia, have a different set of species, which are dryresistant or require a warmer climate, such as various species of cedar, acacia (nilotic acacia, gum arabic), rosewood, or eucalyptus (Cabi 2013, 29, 116, 149, 175, 206), but also species of warm temperate zones, such as alder (Cabi 2013, 63). Equatorial South Asia shares several of these trees, such as species of acacia, but also has a unique set of trees, which are adapted to the hot and humid climate, including, e.g., sandalwood, white or Indian siris, or white cheesewood (Cabi 2013, 53, 66, 434). Wood, woodworking, and the use of various sorts of wood is an area where cultural history may contribute a great deal to the knowledge of prehistory, due to the decomposition of the materials, the subsequent scarcity in the archaeological record, and its continuous frequent usage through history. The trees have different qualities, which make them unequally suited for various purposes. Inherent characteristics of trees include weight, ease of lumbering, woodworking, and carving, durability, wiriness, flexibility, ability not to shatter or break under pressure or during working, movement during drying, speed in drying, and ability not to rot or decompose in contact with water, humidity, or insects. The wood of elm is middleweight and soft but less resistant to rot and insects and therefore mainly used for indoor carpentry, but also for, e.g., handles. However, the elm is easily affected by disease and therefore less frequent during periods of elm-sickness. The wood of ash is, like elm, susceptible to rot and insects, but the tree is heavy, hard, and flexible, with high strength, and is therefore used for implements that require strength, such as oars, frames, constructions, handles, and spears. The use of the birch in historical times includes all its parts: the wood was used for producing coal and for firewood; the wood was also used to manufacture houseware of various kinds, such as handles and furniture; the bark was used for roofing; and the sap for medical purposes. The wood of oak is heavy, hard, and strong and the heartwood is highly resistant to rot and insects – oak heartwood can remain for hundreds of years under water, becoming what is known as black oak. Therefore, oak is preferred in all types of objects in frequent contact with water, such as boats, barrels, and bridges, but also plows, as well as furniture, and parts of buildings with a demand for high strength, such as doors and gates. Beech, like birch, is a very frequent tree, found in all Europe and Northern and Western Asia, and very important in everyday use, e.g., for firewood. The tree is strong, middleweight, and dries quickly but also cracks easily, is unstable to moisture movement, and is non-resistant to rot and insects. Besides being used as firewood, beech was also used for furniture and carpentry (Boutelje and Rydell 1995, 185–204, Andersson and Granlund 1966, Cabi 2013, Mallory and Adams 1997, 599–601). Several of these trees are important in mythology. Specifically oak and ash are mythic trees, which have the function of cosmic trees, which are the pillars of the firmament. This is found in Germanic myth (the ash tree Yggdrasil), as well as in mythologies in the Caucasus and Central Asia (basically oak), and these trees were worshipped as deities (Gamkrelidze, Ivanov, and Winter 1995, 527 ff.). As for language, there are several potentially interesting aspects here. The first is the generic term wood. The second is the various tree species and their reconstruction, a matter of debate for more than a century in Indo-European studies (cf. Pereltsvaig and Lewis 2015). Besides the controversy surrounding the Indo-European homeland question and the relevance for the reconstruction of tree species, the issue is interesting from another perspective. It is noteworthy that the species of trees have remained so consistent, not just the generic terms for tree or wood. This is probably due to the vital characteristics of the tree species as relates to cultural activities, e.g., for building boats, houses, and walls; to prepare shafts of arrows and spears; or as containers for liquids. Even though our corpus of trees is smaller than for the other concepts in general (e.g., it does not include Caucasian data), we can see some tendencies. First, there is a substantial differ-

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ence in semantic instability and productivity between the material wood and the various tree species. Tree species remain remarkably constant with very few changes, whereas wood is highly unstable, in particular in meaning change. We may reconstruct roots for the material wood (e.g., PIE *doru-, *derwo- ‘wood, tree’), but there are multiple parallel tracks and lexical substitution in branches and languages, which are etymologically intertwined with several other roots, including ‘forest’ or ‘field’. Apparently, wood is a cyclic concept, where etymological explanations mirror attested meaning changes (see 6.13). The common trees have reliable reconstructions in Indo-European, which are well known (see appendix 3b). In colexification and meaning change, wood has a huge number of connotations, both colexifications and changes (appendix 3b). These include specializations to species, e.g., lime-tree, alder, poplar, mulberry, oak, other wood-related materials, e.g., timber, lumber, materials, items made from wood, e.g., log, stick, pole, metonymic changes to weapons or implements made partly from wood, e.g., club, lance, sickle, hoe, scythe, various items built with wood, e.g., ship, fort, stronghold, building, room, mast, meanings relating to the origin of wood, e.g., bush, forest, shrub, field, or reference to the labor caused by wood, e.g., work, act, deed, business. In all, the richness in connotations of wood imply the overall cultural importance of wood, reflecting the entire process of wood working, from identifying the trees in the wild, to lumbering, woodworking, construction, building, and finally its monetary importance. For the specific tools related to woodworking, i.e., axe, saw, and knife, see 6.6.3.

6.9.2 Metallurgy The earliest phases of metal use trace back to Neolithic times, where oxide of iron, hematite, and copper materials were used for decoration and ornamentation, e.g., on pottery. This practice was not metallurgy in the true sense, since we do not talk of melted ore, formed into objects. The earliest traces of metallurgy date back to Anatolia and Iran 10,000–8,000 BP, by means of archaeological remains of small copper objects. This early copper may have been derived either from melted native copper or smelted ore. The native copper is very heterogeneous, containing silver, arsenic, nickel, lead and other materials, but there is evidence for heating and purification of the copper already in this early phase. Further, meteoric iron was known to Neolithic people, but they were not capable of melting it, due to the high temperature required for melting iron. Native iron and native copper both share the problem of cracking when cold-hammered. Gold must have been known to Neolithic peoples, but there are no objects of gold which predate 6,000 BP (Mallory and Adams 1997, 380, Tylecote 1992, 1–6). Normally, the period labeled Chalcolithic or Early Bronze Age is considered to mark the beginning of metallurgy in Eurasia. However, the technology of smelting copper was known previously, and the Chalcolithic marked a wider spread of the technique, also including more industrialized mining, rather than an invention of a new technology. By 6,000–5,000 BP the procedure of smelting copper was widespread, and artifacts are found, in successive time order, from Mesopotamia, Egypt, Anatolia, Central Europe, Caucasus, and the Steppe area (Tylecote 1992, 7–34). The further spread of copper smelting in Europe emerged from the Balkans, and is implemented in northern Italy by 5,000 BP, in the TRB culture in Northern Europe. Normally, the development of bronze, a combination of smelted copper and tin, is supposed to mark the transition to the Full Bronze Age. As with the transition to the Chalcolithic, these technologies were already in use before, and the transition in technology was more gradual than a leap. The Full Bronze Age marked an industrialization of metallurgy, with a large increase in a number of bronze artifacts, as well as the technological advancement of furnaces for smelting (Tylecote 1992, 35–46). Gold has a history of its own. First, gold as a material is a bit reminiscent of wood; it is seldom preserved in its original shape in the archaeological record, due to its high value, its uselessness for tools and weapons, and the ease of melting and coldhammering. The only known technology of the Neolithic and Chalcolithic periods for preparation of gold was mineral dress-

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ing, i.e., grinding the quartz rock to release gold particles, which were then extracted using a water stream. It is difficult to tell exactly when gold became the most desired of metals, a standard for measuring value of all items. It is known from both the Neolithic and Chalcolithic periods to be used in all sorts of ornaments, for instance on statues or weapons, often as tin sheets, leaves, or granulation, something which indicates a high value and uniqueness: the metal had to be spared and used as effectively as possible (Tylecote 1992, 44–45). The metal silver has a different history, having been implemented considerably later than copper and gold. Native silver is rare, and most early silver was derived from lead, a process that involves heating to a level of 900–1000 °C. Silver objects are found in Egypt and Mesopotamia around 5,500 BP, in Crete and mainland Greece around 4,500–4,000 BP, in the North Caucasus around 5,000 BP, and in Yamna graves from the same period. The wider use of the metal iron began later than copper, bronze, and gold. The processing began in Asia Minor around 4,000 BP, but it is likely that iron occurred already during the Bronze Age at the bottom of furnaces as a result of smelting of copper ore. The metal iron existed earlier than that, but only in the form of meteoric iron or single artifacts out of any industrialized context. At its first occurrence in Asia Minor, iron was used for small pieces of jewellery, but already here, dagger blades are found. Gradually, its use in weapons increased, and by 3,200–3000 BP, it was implemented on a larger scale in the entire Anatolian-Iranian area. During the centuries following after that, iron quickly spread to the east, west, south, and north, e.g., in Palestine around 3,000 BP, Greece 2,900 BP, Egypt 2,800 BP, Europe 2,800 BP, and Britain about 2,500 BP, marking the entrance of the Hallstatt period. Moving eastwards, the iron reached India and possibly also China, about 2,400 BP. The processing of iron was the important innovation of the spread: wrought iron was produced by reduction of iron ore to solid, pure iron at 1,200 °C, which required the use of charcoal (Tylecote 1992, 47–60). Culturally, the use of these metals in historical times is highly variable, depending on the inherent quality of the metals. Culturally, metals are, due to their use, connected to the areas of weaponry (6.10.1), tools (6.10.2), tillage implements (6.6.3), and woodworking (6.9.1). Copper and bronze, and later predominantly iron, had practical as well as martial functions, used for spearheads, arrowheads, swords, knife blades, armors, and shields; but also for cultural implements such as plows, spades, hoes, needles, and so forth. Besides, these metals were used for ornaments, filigree, decoration, jewelry and smaller objects, and coins. Gold and silver were mainly used for decoration, ornaments, filigree, jewelry, and smaller objects. During antiquity, gold and silver became important ratified standards of value, through the emergence of the practice of embossing coins, which began in Lydia but spread very swiftly through the antique Mediterranean world and further east, south, and north (Howgego 1995, 17 ff.). In mythology, metals occupy a special position. Most noteworthy is the Greco-Roman myth of the world ages, which is paralleled in the Old Indic myth about the yuga. In Greco-Roman myth, the golden age is a period of total lightheartedness, where humans lived free in total equality, without diseases; the earth gave everything they needed; humans enjoyed their work, and died peacefully sleeping. The silver age meant a considerable deterioration: life of humans became shorter, the earth gave less abundance, humans discovered sin, but still, they sacrificed to the gods. The third, or brazen age, meant an introduction of war by the gods to humans, and the gods rejected the fruits of the earth, due to the hardheartedness and violence of the human race. However, weapons were still made of ore, and iron was not yet invented. This is described as the age of the heroes, which improved the conditions of humans, fighting against dark forces. The fourth age was described as the iron age, the worst of ages, where distress never ceased, and in the end humans would be born with grey hair, family and friend ties would be dissolved, parents and elderly people are not respected, fist right dominates, oaths are broken, and finally, evil dominates earth, and only suffering remains (Roscher 1897–1902, 6: 375 ff.). Old Indic myth about the four yuga (krita, tretā, dvāpara and kaliyuga), which are also described in terms of metal and color, reflects the Greco-Roman myth of a decay (Glasenapp and Carlstedt 1976, 142–

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Figure 42: Borrowability (x), semantic instability (y) and cognacy (node size) for METALS.

145, Monier Williams 1993), forming an interesting parallel. This mythology complex gives an indication of the values of the metals, which must go back considerably in time, also connecting to the martial sides of copper and iron, which may be connected to the industrialization of warfare during the Chalcolithic age (6.10.1). For our corpus, we have investigated the four most important metals, copper, iron, silver, and gold. Gold, copper and silver can be reconstructed to the Indo-European proto-language (PIE *ǵhelh₃-to- ‘gold’ < PIE *ǵhlh₃- ‘green, yellow’; PIE *h₂éi-es- ‘metal, copper, bronze’; PIE *h₂erǵ- ‘brilliant, white’). For silver, the migratory proto-form *silubhr- is also dominating, whereas iron shows different tracks, mainly leading to roots meaning ‘red’ (e.g., PIE *h₁ēsh₂rno- ‘bloody, red’). In Caucasian, the metals gold and copper can be reconstructed; and the etymologies are almost completely intertwined (PKv *okʰr-o ‘gold’, PD *dokʰ- ‘brass, copper’; PKv *satʰ ‘gagate’, PNWC *daśw- ‘gold, silver’, PD *sed- ‘gold’, PN *daš- ‘gold’ PKv *ʒar- ‘kind of gold’, PNWC *ǯăr- ‘steel’, PD *ʒər- ‘copper, bronze’; PKv *basr- ‘steel’, PNWC *wăsw- ‘copper’, PD *wəswar- ‘gold’; PKv *bekʰ- ‘copper’, PD *bakʰ-e ‘copper’, PD *kʰeb-o ‘lead’; PKv *pʰas-a ‘manganese’, PNWC *pʰšʲa ‘red’, PD *pʰaχ-e ‘red copper’; PKv *rwal- ‘copper’, PNWC *ωwa- ‘copper’; PKv *lenʒ- ‘copper’, PNWC *daʒ-ən- ‘silver’, PD laʒ-, *leʒ- ‘copper (red or yellow), iron’, PN *jeʒ- ‘yellow copper’; PKv *c’akʰ- ‘copper’, PD *c’ah-a ‘arrow; bow’). The etymologies for iron are distinct from gold, but overlap with copper as well as various weapon terms (PKv *ar- ‘kind of iron’, PD *hər- ‘iron, copper’; PKv *ɣoč’- ‘iron fish-fork’, PNWC *ωwăć-a ‘iron’, PD *ωuc’:-e ‘copper’; PKv *zod- ‘melted metals’, PD *zido- ‘iron’; PKv *rk’-in- ‘iron’, PN *dik’ ‘axe’, PD *rik’‘iron’; PKv *max- ‘metal; metal weapon’, PNWC *maxw- ‘metal hoe’, PD *max- ‘iron; pearl’, PN *max-a ‘nail’). Silver etymologies lead to both gold, and copper, but also to other meanings, such as ‘coin’ (PKv *tʰetʰw- ‘white; silver coin’, PNWC *tʰătʰw-a ‘silver, gold’, PN *datʰew- ‘silver’; PKv *liʒn- ‘copper’, PNWC *rəʒən- ‘silver’, PN *jeʒ- ‘yellow copper’; PKv *wecʰx-il- ‘silver’, PD *ωarcʰ- ‘silver’). In our corpus, our metals cluster together in colexification and meaning change (fig. 43). As expected, the network informs us about additional concepts that we should have included: nodes at the center of the graph include other metals, e.g., ore, bronze, metal, brass. The most important clusters of meanings refer to wealth and property, e.g., money, wealth, currency. Other connotations are also predictable: steel, sword, tool, toughness (by iron), bright colors, e.g., shining, white, blonde, brilliant, yellow, or various stray objects of metal, e.g., metal wire. In addition, metals have low rates for instability and borrowability (fig. 42).

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Figure 43a: Colexification and meaning change for METALS (Indo-European).

Figure 43b: Colexification and meaning change for METALS (Caucasian).

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Map 46a: Cognacy map for the concept copper (modern languages).

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Map 46b: Cognacy map for the concept copper (ancient languages).

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Map 47a: Cognacy map for the concept iron (modern languages).

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Map 47b: Cognacy map for the concept iron (ancient languages).

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Map 48a: Cognacy map for the concept gold (modern languages).

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Map 48b: Cognacy map for the concept gold (ancient languages).

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6.9.3 Products of the processing of wood, stone, leather, skin In our previous chapters, we have frequently mentioned the difference in behavior between products of food and clothing (honey, hops, milk, salt, wax, wool) and products that are a result of hunting or slaughtering (meat, grease, fur) or products that are a result of processes that involve more force in the preparation (stone, wood). The two latter types we treat as a separate class, which we label materials. The concepts of this class are characterized by a very high semantic instability and rich cognacy, equivalent to our most extreme classes, e.g., game animals (fig. 13). We consider this result to be noteworthy, in particular since three of these terms are in the Swadesh 100-list (meat/flesh, grease, and stone). The borrowability is relatively low, but the semantic instability is extremely high (fig. 39).

6.10 Weapons and warfare The prehistory of weaponry is interesting from multiple perspectives, and relates to several other cultural materials and practices, such as metallurgy (6.9.2), woodworking (6.9.1), hunting (6.4), and transportation (6.11). From prehistoric periods, weapons can be studied from the perspective of the artifacts themselves, i.e., weaponry and technology, of which normally only the parts of stone, bone, or metal, such as spearheads, arrowheads, knife blades, and axes have survived, whereas the tree parts have been decomposed. The other perspective is to study the morphology of their impact, typically by means of injuries and fractures on human or animal corpses (Hutchings 2016). The level of warfare and human violence in the Neolithic period in Europe, Anatolia, and Mesopotamia is an old controversy. According to one theory, Neolithic Europe, labeled “Old Europe”, was a peaceful, matrilineal culture, which was destroyed by the coming of the warseeking, patrilineal Indo-Europeans from the Russian steppes during the early Chalcolithic (Gimbutas 1974). Another theory (see Beyneix 2012 for an overview) views the Neolithic revolution as period introducing warfare in relation to hunter-gatherer societies, due to the population increase following upon the sedentary agricultural practices. Both theories are probably oversimplified. There is plenty of evidence of weaponized violence during the Neolithic period, traceable from skeletal material and weaponry, from both Europe, e.g., France and British Isles (Beyneix 2012, Mercer 2006), and the Levant (Shimelmitz and Rosenberg 2013); however, the conflicts were more small-scale, mainly constituted by armed duels, ambushes, murders, or smaller raids. At least in the European (France, Britain) record, most injuries and fractures are caused by arrows, indicating that the bow and arrow were the most frequently used weapons in human conflict. Evidently, more large-scale conflicts emerged first in the Chalcolithic period, where societies became more hierarchical, and weapons were manufactured at a more industrial scale. First from this period, we have skeletal remains, which indicate mass-based killings by war-like enterprises (Beyneix 2012, Mercer 2006). In our lexical corpus, we have investigated mainly weapon terms, spear, bow, arrow, knife, and sword. We have not studied the general abstract terms for war and peace, which would have been interesting as well. In etymologies, weapons are highly intertwined with implements, which are also complex and rich in lexical substitution and semantic change. However, we have classified weapons and implements into two categories, even though the categories are overlapping (see appendix 3b). We may reconstruct most of our weapons, at least arrow, bow, spear, knife, and axe both to Proto-Indo-European, Caucasian families, as well as to Proto-Uralic. However, all concepts are rich in lexical substitution and meaning change. Further, weapons score high in borrowability (fig. 44), but they score lower in semantic instability than their closely related implements (fig. 30b). The colexification and meaning change network by weapons (fig. 45) is both rich and complex. Nodes at the center give both complementary weapons, e.g., lance, dart, dagger, spear-

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Figure 44: Borrowability (x), semantic instability (y) and cognacy (node size) for WEAPONS.

head, javelin, club, as well as concepts relating to the oblong shape, e.g., pole, flute, reed, vein, pipe, straw, but also ray, beam, lightning. Connected to bow we have the corresponding concepts arc, arch, rim, crescent, mountain range, but also crooked, bent. Further, we find verbs relating to eagerness, e.g., to hurry, to strive, to drive, and all over the network, we find meaning relating to the sharpness of weapons, e.g., tip, thorn, prick, sting. Interestingly enough, only as an exception we do find metaphorical changes referring to martial connotations, by embodiments such as penis (by sword) or reference to the devastating result of warfare, e.g., massacre (by sword).

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Figure 45a: Colexification and meaning change for WEAPONS (Indo-European).

Figure 45b: Colexification and meaning change for WEAPONS (Caucasian).

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Map 49a: Cognacy map for the concept sword (modern languages).

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Map 49b: Cognacy map for the concept sword (ancient languages).

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6.11 Transportation 6.11.1 Draft animals The innovative use of livestock for the purpose of traction belongs to the Secondary Products Revolution (6.6.1), which began in the Near East during the early Chalcolithic and then spread successively in all directions. As mentioned earlier, the Secondary Products Revolution, compared to the first Neolithic Revolution, was more of a dispersed revolution, where various innovations, such as the domestication of the horse, took place outside of the original Neolithic core area, Mesopotamia and the Near East (Greenfield 2010). Within the domains of animal transportation, there were two vital innovations, which emerged in different locations, north and south of the Black Sea respectively. The first was the use of domesticated animals, which previously were used mainly for consumption, for traction. Here, the bovine cattle, due to their size and strength, must have been favored over the other animals. A significant development was the traction of an implement similar to a hand-held hoe, resulting in the plow (see 6.6.3). Another equally important innovation was the wheel and the wagon, pulled by animals (6.11.2). However, prior to these innovations, animals must have been used for carrying burdens and other types of traction, something that is difficult to prove from the archaeological track record. Zooarchaeological evidence, e.g., traction-associated pathologies, indicate that bovine cattle were used for traction already during the Neolithic, but that this exploiting mainly targeted female animals. During the Chalcolithic, after the introduction of the plow and the wheel, the male animals were mainly used for traction (Greenfield 2010). The earliest evidence for the plow is from Mesopotamia, in the form of plow marks around 7,000 BP. More substantial evidence, in the form of textual and pictorial evidence, come later, stemming from the Chalcolithic period (Greenfield 2010). In Europe, the earliest certain plow marks are from the Corded Ware culture 5,500 BP. A likewise important innovation is the yoke, used to harness a pair of draft animals in front of the draft object (plow, wagon or anything else). The earliest evidence for yokes are from the Chalcolithic and Early Bronze Age, stemming from various sites in the Near East and Europe (Greenfield 2010). The equine animals, e.g., horse and donkey, follow a separate domestication line, and so does the use of equine animals for traction. As with the other domesticated cattle, the earliest evidence for horse domestication is problematic, since it is not always clear from the skeletal material whether a horse is wild or domesticated. During the mid-Holocene (≈ 9,000 BP), wild horses were found in Europe, Caucasus, and Anatolia, and they were occasionally hunted for their meat. However, around the period of their domestication, wild horses diminished dramatically and were successively pushed eastwards, until they were made extinct in all of Eurasia except for Mongolia (Clutton-Brock 1987, 80–90). Therefore, at the period of the earliest domestication, horses were most frequent in the Steppe region and eastwards, where three distinct wild species were available. It is also here, in the Caspian steppe around 6,800 BP, that the early remnants of domesticated horses are most common. Domestication can be concluded from pathologies of horse skeletons, such as marks of bridle-type implements on the horses’ teeth (Anthony 2007, 198 ff.). According the Yamna theory of Indo-European origin, the domestication of the horse was a significant innovation of the Pontic-Caspian Steppe region, which marks the beginning the dispersal of the Indo-European family from here and to the north, west, and south. Interestingly enough, the domestication of the donkey, for a purpose very similar to the horse, i.e., traction and riding, took place at approximately the same time, ≈ 7,000 BP, but in a different region, the Nile Valley. The wild progenitor consists of two different African wild donkey species, which show domestication-associated pathologies at the earliest during this period (Marshall and Weissbrod 2011). In mythology, the horse played a prominent role in Indo-European culture, in particular through the practice of horse sacrifice, paralleled in Ancient India and in the Celtic area. The

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Figure 46: Borrowability (x), semantic instability (y) and cognacy (node size) for DRAFT ANIMALS.

horse was a highly valued animal for sacrifice, which was important for establishing order and controlling productivity (Puhvel 1987, 269–276). Our study of animal transport includes animals used for traction. In this paragraph, we consider the horse and the donkey, whereas ox has been discussed with the bovine cattle (6.5.5). Vehicles are dealt with under a separate paragraph (6.11.2). For Indo-European, we can reconstruct a common root for horse, found in most branches (PIE *h₁eḱwo- ‘horse’). There is some lexical substitution in branches and languages, but in general, horse terms are relatively stable, both in terms of borrowability and semantic instability (map 50, fig. 46). Caucasian languages also have reconstructed roots for horse, but with some overlapping with donkey (PKv *k’wicʰ- ‘foal’, *gwəć-, PNWC *gwəś- ‘donkey, mule’, PD *gwacʰ‘jenny (donkey)’; PKv *šaš- ‘steed’, PN *eššə’ ‘horse’; PKv *čʰu-, *a-čʰu- ‘horse’, PNWC *čʰə ‘horse’, PN *tʰ:o ‘horse’, PD *a-čʰwi ‘horse’). For donkey, the migratory term proto-form *osonos ‘donkey’ dominates the map (map 51). Besides, many etymologies, both in Indo-European and Caucasian, are derived from horse-roots (see appendix 3b). In terms of colexification and meaning change (fig. 47), horse and donkey group close together, representing the central nodes of a network of shared additional meanings. Besides various specializations, including, foal, stallion, mule, mare, ass, we also see meanings referring to the gelding, e.g., gelding, the role as draft animals, e.g., burden, pack, load, or metonymic meanings such as saddle, harness. Metaphoric human embodiments are relatively rare, but we have, e.g., lucky person, enviable person, messenger (by horse), and fool, jackass (by donkey).

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Figure 47a: Colexification and meaning change for HORSE and DONKEY (Indo-European).

Figure 47b: Colexification and meaning change for HORSE and DONKEY (Caucasian).

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Map 50a: Cognacy map for the concept horse (modern languages).

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Map 50b: Cognacy map for the concept horse (ancient languages).

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Map 51a: Cognacy map for the concept donkey (modern languages).

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Map 51b: Cognacy map for the concept donkey (ancient languages).

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6.11.2 Vehicles The time and place of the invention and spread of the wheel and wheeled vehicles is a much discussed topic in archaeology and historical linguistics. To several theories, such as the Yamna theory, the horse and the wheel were significant innovations, which may explain the rapid spread of the Indo-European language family from the Pontic-Caspian steppe and to the east, west, and south (Anthony 2007). However, the place and exact time of the origin of the wheel, and in particular its use in wheeled vehicles as a means of transportation, remains obscure. The earliest wheels, hubs, and axles were produced by wood, a non-durable material (6.9.1). What seems to be evident, though, is that the invention and diffusion of the wheeled vehicles in the Chalcolithic period 5,500–5,000 BP, was so rapid that the ultimate origin is, and probably also will continue to be, hidden in darkness. At least, it is difficult to trace the origin by archaeological evidence (Piggott 1983). The earliest evidence of wheeled vehicles in the Near East is in the form of cuneiform symbols from Late Uruk (5,300–5,100 BP). However, it is evident that even though the innovation of the wheel was there, it was not of great importance, and sledges were used besides wheeled vehicles for transportation (Greenfield 2010, Anthony 2007, 65–67). Various types of evidence for wheels and wheeled vehicles are found in the archaeological track record from multiple sites in the period 5,700–5,000 BP, such as Eastern Europe (Yamna culture) 5,500– 4,500 BP, Central Europe (Baden culture) 5,500–5,000 BP, Southern Poland (TRB) 5,700– 5,100 BP. Most of these early vehicles were likely heavy and slow, pulled by a pair of yoked oxen and used for transport (Greenfield 2010). Another important early use of the wheel was for the purpose of pottery, which originated in Mesopotamia around 5,500 BP and spread to the Levant and Egypt, where it was introduced around 4,600 BP (Doherty 2013). In comparative linguistics, vehicle terms belong to the most discussed and investigated among vocabulary, in particular for Indo-European (Fortson 2010, Anthony 2007). Here, we investigate four vehicle concepts, wagon, wheel, axle, and hub. It is evident that all these terms can be safely reconstructed to Proto-Indo-European (Mallory and Adams 2006, 247). In branches and languages, there is a considerable degree of lexical substitution and parallel etymologies (appendix 3b), and considering the explanations and derivations of these etymologies, we should consider all vehicle terms to be circular in their semantic evolution (see 6.13). The core of the discussion on the words for wheel is whether the meaning of wheeled transport is primary (and therefore reconstructable to the proto-language) (Heggarty 2014). In addition to this discussion, we may consider the result of our evolutionary test for the two Indo-European wheel roots, of PIE *kʷel-o- ‘wheel, circle’ (79981) and PIE *Hróth₂o- ‘wheel, circle’ (80116) (table 38). For PIE *kʷel-o-, the only meaning with a higher probability is ‘wheel’ (0.93), for PIE *Hróth₂o-, the meaning with the highest probability is ‘wheel’ (0.99), but also ‘chariot’ (0.86) and ‘wagon’ (0.86) are likely. Even though our development of a methodology of semantic reconstruction is still in progress (Carling, Hammarström, Cronhamn, Farren, et al. Forthcoming), we believe that the reconstruction is an additional argument in favour of wheeled vehicles for Indo-European. The Caucasian etymologies show interesting parallels to the Indo-European ones. We find parallel derivations, e.g., for wheel from the verbal roots of the meaning ‘to turn’ (PKv *gor‘wheel; to roll’, PN *gur- ‘wheel’, PD *gur- ‘to whirl, to roll; wheel’; PKv *bor- ‘rotation’, PN *bora ‘mill’s wheel’, PD *bor-a ‘wheel’). Several vehicle terms can be reconstructed, e.g., wagon (PKv *sa-kʰum- ‘carriage’, PNWC *kwə ‘carriage, cart’, PD *hankʰwə- ‘carriage, vehicle’), and yoke (PKv *uɣ-el- ‘yoke’, PNWC *ɣəw ‘yoke’, PD *ur- ‘yoke’). All vehicle terms score high in both borrowability and semantic instability, with one important exception, yoke, which we have sorted under vehicles (see fig. 48, map 53). Yoke is an extremely stable term, equivalent to wool or salt in our corpus. In colexification and meaning change charts (fig. 48), the vehicle words (excluding yoke) cluster together, forming a rich network with a large number of of additional meanings appearing at the center of the network, including nave, spindle, pole. For the remaining changes, they

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Figure 48: Borrowability (x), semantic instability (y) and cognacy (node size) for VEHICLES.

are more individually connected to the various concepts. By hub we have, e.g., skull, head, by nave we have, e.g., center, relationship, origin, family, navel, middle. Wheel leads to, e.g., sun, circle; axle leads to, e.g., spindle, stake, pole, axis, celestial axis; wagon leads to, e.g., chariot, vehicle, but also sky, firmament, axis. It is noteworthy how frequent connotations and metaphorical changes involving the body and the sky are with vehicles. This indicates that vehicles had a prominent position in the culture.

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Figure 49a: Colexification and meaning change for VEHICLES (IndoEuropean).

Figure 49b: Colexification and meaning change for VEHICLES (Caucasian).

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Map 52a: Cognacy map for the concept wheel (modern languages).

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Map 52b: Cognacy map for the concept wheel (ancient languages).

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Map 53a: Cognacy map for the concept yoke (modern languages).

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Map 53b: Cognacy map for the concept yoke (ancient languages).

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6.12 Numbers and measures 6.12.1 Ordering of time A shift from the foraging of hunter-gather subsistence to agriculture is also generally considered to imply a shift in ideology, from a more egalitarian, small-scale system, based on animistic belief, spiritual myths, and totemism, to a system that is more hierarchical and large-scale. Agricultural societies have a system oriented towards kin and reproductivity, aiming at maintaining existing structures. They also have a commonly developed cosmology of a deistic system of sky gods, which includes concepts of order and disorder and a general anxiety over the disruption of the order and its consequences. The maintenance of the order involves a system of practices, rituals and rules, which need to be performed at specific times and in a specific order, in order not to invoke the wrath of the deities. This system is first believed to develop in PPNA of Southwest Asia, as a direct result of the agricultural revolution (Barker 2006, 407–410, Kohler et al. 2017, Hodder 2010). A more detailed ordering of time, distinguishing and measuring seasons, days, and hours, is a vital part of this system, directly connected to the agricultural practice and its connection to the vegetation year. It is difficult to reconstruct the systems of time reckoning used by ancient farming societies through the archaeological record. Systems that are more elaborate developed first during the Bronze Age, which we know of through ancient Sumerian, Babylonian, and Greek sources. It is unlikely that these elaborate systems of the Babylonians and the Ancient Greeks, which is paralleled in, e.g., ancient India, emerged out of nothing. Ancient, nonliteral farming societies likely had developed systems of time reckoning, which connected the deities to cosmology and the vegetation year, impacting feasts, rituals, and other religious practices. Unfortunately, little research has been done in the area of ethnoastronomy or archaeoastronomy, investigating the role of development of agriculture to time-reckoning (Nilsson 1960, Ruggles 2015). Of high interest in this context are number systems of individual languages as well as in families, which we do not include here (Gvozdanović 1992). A further domain of particular prominence is names and connected functions of deities, which in itself is an independent theme, also connected to the reconstruction of poetic and religious language (Watkins 1995, Gamkrelidze, Ivanov, and Winter 1995). Another semantic domain of interest is words for natural ordering of time, such as names for days, weeks, months (lunar phases), seasons (divisions by weather, light, climate, etc). We have focused on the terms for the seasons, which are of importance in an agricultural society due to their connection to the farming cycle. Most Indo-European ancient cultures had a four-division season system, involving spring, summer, autumn, and winter, connected to the four cardinal directions. A three-division system is found in Hittite (ḫamešḫa-, ḫamešḫant‘spring’, zēna- ‘autumn’, gimmi, gimmant- ‘winter’), which some researchers believe to be the reconstructed Indo-European system (Proto-Indo-European *ues-r/n- ‘spring’, *smH- ‘warm season’, *ǵh(e)im- ‘winter’) (Nilsson 1960, Gamkrelidze, Ivanov, and Winter 1995, 750). We see some tendencies in our data. For Indo-European, we may reconstruct terms for spring, summer, and winter, but there are several parallel tracks and a certain degree of lexical substitution (maps 54–56). In particular, there is intertwining of the etymologies for spring with year, summer, and early, and in particular between autumn and harvest (appendix 3b). Winter is a very stable word, which is etymologically intertwined with cold. The terms are inherent in both Indo-European, Caucasian, and Uralic (appendix 3b), and in borrowability and semantic instability, all seasons score low (fig. 50). The colexification and meaning change network of seasons (fig. 51) is very interesting, in particular since there are nodes and links that connect them all together, of which the most important are season, year. Beginning with autumn and summer, we notice that they are tightly connected, also including a third node, harvest. An additional cluster here involves meanings

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Figure 50: Borrowability (x), semantic instability (y) and cognacy (node size) for SEASONS.

close to harvesting, e.g., to cut, cutting, reaping, slaughter, mowing, incision, fruit. Independent of this cluster and connected to spring, we have meanings such as to burst, to spring, to explode, to jump, to strike, to bump, origin, but also mirage, spirit. Connected to summer we have flame, energy, fire, glow, heat, warmth. Winter connects to storm but also to autumn and harvest.

6.12 Numbers and measures

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Figure 51a: Colexification and meaning change for SEASONS (IndoEuropean).

Figure 51b: Colexification and meaning change for SEASONS (Caucasian).

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Map 54a: Cognacy map for the concept winter (modern languages).

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Map 54b: Cognacy map for the concept winter (ancient languages).

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Map 55a: Cognacy map for the concept spring (modern languages).

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Map 55b: Cognacy map for the concept spring (ancient languages).

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Map 56a: Cognacy map for the concept summer (modern languages).

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Map 56b: Cognacy map for the concept summer (ancient languages).

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6.13 Discussion: Vocabulary Our lexical data is interesting from several viewpoints. The first perspective is the vocabulary itself, including the variation in colexification patterns, meaning changes, borrowability, cognacy stability, or lexical substitution, which we assume to mirror the functionality of these artifacts or activities in their cultural systems. The second aspect, which is connected to the change behavior of concepts, is the geographic distribution of cognates, including both widespread homoplasy as well as patterns of divergence. The third aspect, which has bearing on our results from grammar, is the lexicon as a proof of prolonged mutual contact between languages. By means of loans and directions of borrowings, we may establish contact zones or areas, which we should regard as complementary to evidence of contact retrieved from grammar. Beginning with the behavior of lexical concepts, we may identify three distinct types in our culture vocabulary corpus. These types define, as described in previous chapters, the difference in change behavior in relation to the cultural function and salience of the artifacts or activities. Based on all data, we calculate the average borrowability and the average semantic instability, respectively, per category or class (see 6.3.1) and plot them against each other (fig. 52, se 6.3.5. for technical description). The result confirms the tendency that we noticed from the behavior of individual concepts with respect to borrowability, semantic instability, cognacy, as well as colexification and meaning change. We may define three distinct classes. The first type, which we identify as concepts of high salience, are characterized by high stability in terms of cognacy, low borrowability, low degree of lexical substitution, as well as low degree of meaning change, both in terms of colexification as well as meaning change. Colexification and meaning change also moves within specific and often restricted domains, where metonymy and in particular metaphoric change is rare. In this group we find most concepts that we have classified as products (table 35), e.g., wax, honey, mead, milk, salt, wool, but also some other stray concepts of other classes, such as wine, yoke, and our trees (wood, ash, elm, birch, etc.). We assume that this high salience of the trees depends on the important role of trees as material, which makes them equivalent to products in their change behavior. This highly stable group also includes the verbs denoting cultural activities (to spin, to sew, to sow, to weave) and the domestic animals, i.e., dog and cat, as well as the season words (harvest, autumn, spring, summer, winter). The second group is characterized by a low borrowability and relatively low cognacy; however, concepts have a higher degree of semantic instability in terms of colexification, semantic extension as well as metaphoric and metonymic changes. In this group we find most of our domestic animals apart from dog and cat (pig, piglet, cow, bull, ox, horse), the metals (iron, copper, silver, bronze, gold), crops (wheat, oats, barley, rye, grain), tillage words, and the predator birds (owl, eagle, raven). The third group is characterized by a high degree of borrowability, high semantic instability, and high amount of lexical substitution, and rich and complex networks of colexification and meaning change. Meaning changes often move far away from the original core meaning of the concepts, including far-gone metaphor and metonomy. Concepts are also often highly variable on these issues, e.g., they may have frequent meaning change and/or high borrowability, or vice versa. This group includes all our wild animals, including predator animals (lion, panther, lynx, etc.), game (deer, wild boar, hare, bison) as well as the products of hunting or slaughtering (fur, grease, meat). Further, it includes implements, in particular sharp ones, such as sickle, and weapons as well as vehicles (wagon, axle etc.). This different behavior of vocabulary is most likely cultural, relating to the specific system of subsistence that we have targeted in our data. On the other hand, it is also possible that the difference pertains to more general or “universal” structures of semantic change, which we will discuss more carefully in chapter 7. A further observation of our lexical data is that there are lexical concepts that are apparently explicitly cyclic in their semantic behavior. For these concepts, the explanations given for the

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reconstructed roots, i.e., the derivations concluded from proto-language morphology (given in our legend texts) mirrors the meaning changes found in attested languages (included in our colexification and meaning change networks). These may be concepts that score high in semantic instability (but not necessarily borrowability) as well as in cognacy (i.e., they have a high number of cognates), and are therefore frequently involved in lexical substitution. Examples are deer, hare, wood, leather, fur, as well as terms for cattle and vehicles. This implies that lexical substitution and meaning change can be high without involving colexification (in our data, meaning change is coded as 0 and thus not visible in the semantic instability scores). This entire phenomenon, which we have observed in our data, is highly interesting, would be worth a separate study, using evolutionary models. Moving over to our second aspect, including lexical loans as a proof of language contact, we see several interesting patterns coming out of our data (map 57). We have to bear in mind, though, that the results are restricted to our presence of data: we have, for instance, low coverage in the South Asian area for vocabulary in general, which means that we see little activity here, where there should have been a high amount of loan events, probably equivalent to the situation in Europe. Also, the result is a residue of access to ancient data. The nodes and arrows marked as ‘Branch/family/proto-language’ represent mainly borrowings prior to the development of literacy, which may be extended in time, depending on the development of literacy. Turkic loans, to take an example, are later than the loans from Latin, yet they are marked as proto-language loans, since they mainly occurred during a period prior to literacy. However, several tendencies are evident in our loan map. First, that Central Western Europe is an area of rich and mutual lexical borrowing, where Latin (and Greek) are completely dominant. In second position in importance comes Proto-Germanic, as well as Proto-Balto-Slavic. The Northern and Western peripheries of Europe are less prominent in terms of source languages: most arrows go in these directions, not from here. The Eastern part of our macro-area is relatively isolated from the Western part: there are few arrows that indicate mutual contact between these areas. In the Eastern part, the flow of impact goes from east and south towards the west and north. In West Asia, including Anatolia, we have traces of mutual contact, going considerably far back in time. This pattern is due to the presence of very early writing, and naturally, this entire area suffers from absence of Semitic languages in our data. Another further interesting metric is the distribution of gender, which is applicable only to Indo-European languages in our data (table 37). We se clear patterns of gender assignment, which are related to the instability and cognacy rates (table 39). First, we can confirm that masculine is the default gender and most frequent in the data. Feminine comes next, followed by neuter. About 5 % of the lexemes are common gender. A large amount of the lexemes of our corpus are animate words, which naturally have one of the sexed genders, mainly masculine but also feminine. Therefore, we mark animacy in table 39. However, the inanimate objects are highly interesting: apparently, classes with a higher instability rate are more likely to be feminine. This is an issue that we will come back to in our concluding chapter. Table 39 summarizes the change behavior of our various classes by the different metrics and gender. This table forms a basis for the general discussion on language and culture of chapter 7.

6.13 Discussion: Vocabulary

Tab. 39: Summary of rates of borrowability, instability and cognacy, and hierarchy of gender assignment for classes (for Indo-European). The levels are estimations based on the distribution of rates of the boxplots in fig. 53–56. Gender hierarchies imply the order of frequency by genders in the Indo-European data, based on table 37. M = masculine, F = feminine, N = neuter. M > F indicates that masculine is more frequent than feminine, M/F indicates that masculine and feminine are equally frequent. The column animacy indicates whether concepts of the class are animate, as opposed to animate (for the evaluation of gender hierarchies). Classes

Borrowability

Instability

Cognacy

Gender (IndoEuropean)

Animacy

ACTIVITIES

Low

Medium

Medium

not applicable

n

CATTLE

Medium

High

High

M > F/N

y

CROPS

High

High

Medium

M>N>F

n

DOMESTIC ANIMALS

Low

Low

Medium

M>F>N

y

DOMESTIC INSECTS

Low

Medium

High

F>M>N

y

DRAFT ANIMALS

High

High

Medium

M > N/F

y

DRINK AND DRUGS

High

Medium

Low

M>N>F

n

GAME ANIMALS

Medium

Medium

High

M>F>N

y

IMPLEMENTS

High

High

High

F>M>N

n

MATERIALS

Low

High

Medium

N/F/M

n

METALS

Medium

Low

Medium

N>M>F

n

PIG RAISING

Low

Medium

High

M>F>N

y

POULTRY

Medium

High

Medium

M>F>N

y

PREDATOR ANIMALS

High

Low

Low

M>F>N

y

PREDATOR BIRDS

Low

High

Low

M>F>N

y

PRODUCTS

Low

Low

Low

M>F>N

n

SEASONS

Low

Medium

High

M>F>N

n

SMALL CATTLE

Low

Medium

High

M>F>N

y

TILLAGE

Low

High

High

M>F>N

n

TREES

Low

Low

High

F>M>N

n

WEAPONS

High

Low

Medium

F>M>N

n

VEGETABLES & FRUIT

Medium

Medium

Low

F>M>N

n

VEHICLES

High

High

Medium

M > F/N

n

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Figure 52: Average borrowability (x), semantic instability (y) and cognacy (node size) per class of concepts.

Figure 53: Boxplot of average rates of borrowability of classes, organized from highest to lowest.

Figure 54: Boxplot of average rates of semantic instability of classes, organized from highest to lowest.

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Figure 55: Boxplot of average rates of colexification of classes, organized from highest to lowest.

Figure 56: Boxplot of average rates of cognacy of classes, organized from highest to lowest.

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Map 57a: Loanword flow map, showing the position of source languages or branches/proto-languages in our data (see 6.3.3, appendix 3d).

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Map 57b: Loanword flow map, showing connections in our data between source and target languages (see 6.3.3, appendix 3b).

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7 Concluding chapter: an integrated view of the linguistic and cultural histories of Eurasia The main aim of this atlas is to investigate the different processes that create divergence, as well as to study how divergence expands in time and space. A further aim is to identify and explain the mechanisms that trigger or alternatively constrain change, as well as the processes that conflate them; something we search for both inside languages as well as in their environment. Besides, we are interested in the linguistic and cultural histories of the past, involving the reconstruction of the realia of ancient proto-languages. Due to the inevitability of change, time produces diversity. Change is not constant; rather, properties’ inherent role and their function in language and society may affect their rates of change. Some features have a higher stability, indicating that they are typically transferred, from one generation to the next, by lineage. Other features are more prone to change, by gain, loss, or substitution; but tendency to drift of these features runs a permanent risk of levelling or conflation due to the operation of convergence or advergence. Further, environmental conditions, cultural change and relocation may affect the rate of change at all levels. Is it possible to identify these causalities of change rates in language? The model by Nichols (Nichols 1992, Nichols 1997) identifies two basic types of languages, spread zone and residual or accretion zone languages. Even though these classifications may be oversimplified and not applicable from a global perspective (Campbell and Poser 2008, 302–329) they have some bearing on the Eurasian context, where they can be immediately connected to the geographic environment: the high-resistant topography of Caucasus and the Basque country are liklely underlying the specific characteristics of these families. But as we have seen in the grammar section (5.8), the development of grammar in relation to geographic zones is quite complex, with conservation zones, hybrid zones and development zones overlapping each other. In our evaluation of data, both grammatical and lexical, we will instead use the basic notion of migratory and non-migratory language types. In principle, migratory languages are more involved in drift, at all levels, with various consquences for the grammar and the lexicon. Nonmigratory languages are less drifty, but the the slow rate of drift in combination with non-migration may result in a large and accumulated diversity, which corresponds to Nichol’s accretion zones. Our data includes Indo-European, Turkic, and Uralic on the one hand, which are migratory languages; we know that these families have relocated several times during prehistory. Basque and Caucasian are non-migratory languages – there are no reliable evidence for any prehistoric relocation or migration of the speakers of these languages. The most visible difference between the two types is found in linguistic density and geospatial extension of the families themselves (map 2). If we look at the geographic distribution of data, we notice that vocabulary follows language family boundaries more strictly, whereas grammar shows higher degrees of convergence behavior. Nevertheless, there are important exceptions. In our grammar data, we may identify different types of properties. First, we have morphosyntactic properties of nouns and verbs, such as tense morphology, gender, definiteness, and case, which are directly bound by matter, i.e., phonological forms of morphemes, as well as by paradigmaticity. These stick more closely to families, areas and branch boundaries – they principally following lineage, are less areal, and in geography, they come out as more divergent. The other group, which is also bound by matter and paradigmaticity, including alignment, and agreement, is much less divergent than the beforementioned group. Finally, we have patterns, i.e., syntactic properties, which are involved in functional interactions but not bound by matter or paradigmaticity, mainly word order, which are convergent or advergent, display higher areality, and come out as conflated in geography. Even inside these domains, there are discrepancies: higher frequency and economy implies higher instability and lower divergence, lower frequency https://doi.org/10.1515/9783110367416-007

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implies lower instability and higher divergence (see 5.8). The outcome of these processes are large discrepancies in the geographic extension of various domains of grammar; but the reality behind, i.e., the complex change processes that have created them, remain obscure, at least from a synchronic perspective. Hence, we may observe that at least in morphosyntax, economy, frequency and high functional interaction contribute to convergence and widespread geographic homoplasy, transgressing boundaries of families and branches and even, in some cases, the boundaries between migratory and non-migratory families (Haspelmath 2008). Here, our observations are in line with previous research on temporal stability of typology (Dediu and Cysouw 2013, Dunn et al. 2011, Dunn et al. 2005). However, our addition of ancient data may contribute to the discussion, for instance concerning the controvery about the causalitites for the stability over time for word order patterns (Dryer 2011, Donohue 2011, Jaeger et al. 2011). In a separate study (Cathcart et al. 2018) we tested, by means of an evolutionary reconstruction model (6.3.7), the areal pressure of the feature variants of our data (based on Indo-European languages only). A clear pattern emerged first after a recoding was performed, distinguishing gains from losses. Features involved in grammatical relations were coded as either simplifying or complexifying, whereas features not involved in grammatical relations, i.e., word order and features pertaining to inflectional typology (agglutination, fusion, etc.), were coded as neutral. The result indicates that simplifying changes (i.e., loss of morphosyntactic features), together with neutral changes (word order change) have a high areal index, indicating that they are more likely to undergo convergence or advergence (cf. fig. 1). Complexifying features (i.e., gain of morphosyntax) have a low areality index, meaning that they are less likely to converge and more likely to emerge in isolation. Since this study was based on a majority of the grammar data presented in this book, we assume that it may explain – though in various ways – the patterns that emerge out of the data. In our data, vocabulary shows a behavior which is different from grammar. In vocabulary, language contact, divergence and advergence can be observed and measured more easily than in grammar (Haspelmath and Tadmor 2009). We know from recent research that change rates in vocabulary (based on basic vocabulary) is slower than in grammar (Greenhill et al. 2017). In basic vocabulary, the most loan-resistant part of the lexicon (even though change rates may be different (Vejdemo and Hörberg 2016, Pagel, Atkinson, and Meade 2007)), drift is constrained by lineage, which makes basic vocabulary useful for establishing language phylogeny and language classification. Therefore, basic vocabulary also typically produces branch-constrained patterns. As we have demonstrated in chapter 6, the discrepancies in the behavior of lexical concepts of our culture lists is huge (see the overview in table 39). We assume that factors such as economy and frequency (like in basic vocabulary), as well as cultural functionality affect the change behavior of these vocabularies. Like in the grammar, we find both features that produce widespread homoplasy, as well as features that produce high divergence. However, the causes for widespread homoplasy in vocabulary are supposedly different from those for grammar. In vocabulary, widespread homoplasy can be caused both by stability, i.e., by lexemes that are inherited and spread over large areas by lineage: examples in our data are salt (map 44) and milk (map 35). Widespread homoplasy can also be caused by instability or borrowability, i.e., by lexemes that are secondarily spread over large areas by borrowing or are wanderwörter: examples in our data is jackal (map 31). These are two disparate processes, which nevertheless yield a similar result in terms of geographic distribution of cognacy. An important difference is the family distribution: the stable type does not transgress family boundaries, whereas the convergent type typically does. For the other words not belonging to one of these types, the geographic distribution is more or less divergent. However, for vocabulary, the procedure that creates divergence is complex, mainly due to the unpredictable impact of culture change. As we have seen in chapter 6, the discrepancies in behavior, also between closely connected concepts, may be surprisingly large. A term for a hunted animal, such as bison or wild boar, may behave completely differently from its domestic counterparts, ox/cow and pig, to which they are tightly connected by colexifi-

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Figure 57: Schematic representation of the different cultural zones, pertaining to CULTURE and NATURE, and their most characteristic behavior in terms of lexical change.

7 Concluding chapter: an integrated view of the linguistic and cultural histories of Eurasia

cation. Wheat and rye, to take another example, two closely connected crops, behave differently with respect to borrowability and semantic instability. In general, high functionality and a presumed high frequency in terms of everyday usage within a family, branch or area, imply high stability, both in terms of low borrowability, low semantic instability, and low level of lexical substitution. The result is geographic blocks of lexical homoplasy, which mainly follow family and branch boundaries. Of high interest is the behavior of lexemes due to their cultural role and functionality. In chapter 6, we classify culture words by their borrowability, semantic instability, colexification, and cognacy, and thereupon, we test statistically the average behavior of the classes in terms of borrowability, semantic instability, and cognacy (fig. 52–56). Even though there is variation between individual concepts of the classes, the tendency that emerges from the average of our classes is interesting. First, we notice that borrowability and the other three metrics (semantic instability, colexification, and cognacy) behave differently. In another study (Carling, Hammarström, Cronhamn, Farren, et al. Forthcoming) we test change rates (loss rates) by the evolutionary model described in 6.3.7. The results correlate positively with the metrics semantic instability, colexification, and cognacy, but the correlation to borrowability is slightly negative. Therefore, we should consider borrowability and semantic instability as separate indices of lexical change. Of the three metrics semantic instability, colexification, and cognacy, the metric semantic instability gives the clearest result. We will therefore refer mainly to this group in our evaluations. Another highly interesting metric is the frequency of the different genders masculine, feminine and neuter in our data (6.13, table 37). In the cluster of our most stable classes, both in terms of borrowability and instability, we find cultural activities (verbs), as well as cultural products, i.e., concepts for items that are eaten, drunk, or manufactured at daily basis. Further, we find small cattle (sheep, goat, etc), pig words, the domestic animals dog and cat, and drink and drugs. Another group of words belong to the same category, namely words pertaining to the nature, such as seasons, (summer, winter, autumn etc), trees, or metal words. We distinguish these as two different types, since they, even if they share similarities, also are critically different in other aspects and belong to two different domains. Beginning with this stable group, we put the words into two main domains, which we, following upon a structuralist tradition (cf. Lévi-Strauss 2002), label CULTURE and NATURE (fig. 57). In another group, characterized by higher borrowability and higher semantic instability, we find objects pertaining to the out-door or large-scale farming space, with cattle, poultry, domestic insects (bee), crops, and tillage. These classes still represent farming activities, but they are culturally distinct from the previous group in the sense that they are connected to the outdoor farming, the barn, and the tillage. We organize this group under the CULTURE domain.

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A third group incorporates materials connected to manufacture (stone, wood), weapons, implements and vehicles. These are classes representing a higher level of labour intensity and technological innovation, and are important instruments and objects in activities involving hunting and war. These classes are high in borrowability and high in semantic instability. Surprisingly enough, considering the average frequency of genders in our data, these classes are dominately of feminine gender. Again, this groups belongs to the CULTURE domain. Finally, we have a group of words that fall under the NATURE domain. This consists of two parts, which are different in their behavior. First, we have game animals, predator animals, and predator birds, which are highly divergent in terms of borrowability and/or semantic instability. Here, we find our taboo concepts, words representing objects targeted by superstition, ritual and worship, such as our wild and hunted animals. These are either low in borrowability and high in semantic instability, or vice versa. An unexpected result we find for the European indigenous predators, such as wolf and bear (6.4.3), which have very low rates both in borrowability and instability, whereas the deer and wild boar, on the other hand, have high rates for instability and low for borrowability (6.4.2). Why do we have these contradictory results? All these animals are hunted and dangerous and would potentially be affected by taboo replacement. A fundamental difference may explain the result: the deer and the wild boar are worshipped and desired, the predators are feared and undesired, and humans cannot, how much they try, impact the existence of these hated animals. Therefore, their designations do not change. As for gender, words of this group are also predominately masculine or neuter. Second, we have the non-animate terms belonging to the NATURE domain, which are metals, seasons, and trees. Lexemes of these groups are stable, they have low rates in both borrowability, instability and cognacy, and words are predominately either masculine or neuter. From this behavior of vocabulary, we can trace the impact of a cultural system, where concepts designating objects or activities connected to the household or the “safe-space” of daily life, such as eating, drinking, or “harmless” manufacturing, e.g., of fabric, are found in the most stable class. In this group, we also find the household animals, cat and dog, as well as the small cattle, goat and sheep. Higher levels of instability and borrowing recurs outside of the farming’s household, by concepts connected to the farming process, such as tillage, crops, cattle, poultry, pig words, and draft animals. In the most unstable group we find artifacts and materials that are related to technology, industry, and war, such as tools, weapons, materials that are the process of hunting, and vehicles. Concepts here have high rates in both instability and borrowability. As mentioned earlier, the dominance of the feminine gender (in Indo-European) is noteworthy and implies that gender assignment can have a cultural explanation: concepts of this group are typical within “male” domains, such as hunting, technology, and war. Our category connected to the wilderness, including the predators, game animals, predator birds and metals show a highly divergent pattern. The nature represents the given environment, which may be changed or altered by cultural activities, such as hunting or forestry. Here, we find highly variating levels of borrowability and instability, but in general, large parts of the concepts have low rates and are dominately either masculine or feminine. The system can be interpreted as a reflection of a structure, with the “in-door” household, the whereabouts of the family, the women and the children, in the centre, the surrounding “outdoor” farmland and further the industry and war in the outskirts of the cultural sphere. The two latter are mainly the “male” zones in a traditional society. We are looking at a very fundamental system for farming societies, where the settlement, the residence of the family or clan, has a central role, representing order and stability as opposed to the nature or the wilderness, which represents chaos and danger. The wilderness has to be controlled by rituals and sacrifices, by the law and order of religion. In language, the system reflects the cognitive perception of speakers rather than the system created to control it. The indoor “safe-space” is steadily reproduced by lineage, generally with little change in inheritance, borrowability and semantic change (fig. 57). The out-door space generates more change, both in terms of borrowing, semantic

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change, and lexical substitution. The industry and war zone is even higher in lexical change. Finally, the wilderness, the sphere of hunting and exploration, gives rise to highly uneven rates of lexical substitution, borrowing, and semantic change, in partly by processes such as metaphor, metonomy and other types of taboo replacement. This dual system of cultural spaces is likely partly cultural, partly cognitive or universal. It should be considered as unique to farming societies, in the respect that it is, on the cultural side, centered on the settlement. In other respects, the spaces reflect fundamental aspects of human behavior, such as the organization of the family or the clan, the role of the mother and the ego as the safe-space of the growing child, something that is, e.g., reflected in the effects of sound symbolism on basic vocabulary (Blasi et al. 2016). Another interesting issue is to identify whether there are differences between our families in terms of change behavior. This is definitely the case; but not always as expected. Beginning with grammar, we notice that an important difference is the higher tendency to divergence in the zones of the non-migratory families languages (Caucasian, Basque). This goes for almost all features except the most converging ones. This observation is not new; it confirms earlier observations on residual languages. However, when it comes to vocabulary, we may notice some interesting differences between the migratory and the non-migratory languages. First, we notice that there is a surprisingly high level of apparent cognacy shared between the Caucasian families (Kartvelian, Nakh-Dagestanian, and Northwest Caucasian) in our vocabulary. Considering the presumed high time-depth of the proposed proto-languages of these families, this is noteworthy. In addition, the relative semantic stability in these families, or conversely, the tendency of change, when present, is interesting. Compared to Indo-European, we notice the absence of metaphorical changes outside of the cultural sphere of the concepts within the etymologies. Take for instance the predators (fig. 15, appendix 3b): whereas Indo-European languages are overflown with metaphorical meaning changes leading in all kinds of directions, in particular human transformations, Caucasian lexemes stay within the animal kingdom, even within the close family of the animals’ species. The tendency for the game animals is similar. Even though we know that Caucasian people feared and worshipped dangerous animals, also in cults involving manto-animal transformations (Gamkrelidze, Ivanov, and Winter 1995, 405 ff.), we see no reflexes of this practice in language. In another study based on our data and using the evolutionary reconstruction model described in 6.3.7, we investigate these change patterns more carefully (Carling, Hammarström, Cronhamn, Svensson, et al. Forthcoming). This study indicates that in Indo-European, metonymic change outside of the semantic domain (summer > kid) is the most frequent type of change, followed by metaphor. In Caucasian families it is the other way round, with metonymy within the semantic domain (e.g., wolf > hyena) was the most frequent change, followed by metonomy outside of the semantic domain. Metaphor is almost absent. In general, this confirms the patterns that is visible in the colexification and meaning change charts. A likely explanation for this difference between Indo-European and Caucasian families is the environmental adaptation of speakers of these languages. The relocation of migratory family languages gives rise to a more frequent need for semantic adaptation and change in the vocabulary of cultural concepts: the continuous exploration of new environments and establishment of new settlements likely has an impact on the vocabulary, in particular the semantic change. Furthermore, the frequent contact with other language groups affects the levels of borrowability and lexical substitution in the vocabulary. Our data reflects the vocabulary of farming and pastoralist societies, and for that purpose, our results may be of secondary relevance to other systems, such as hunter and gatherer societies. Farming, as well as pastoralism, represents a system that has a long history both within the families of non-migratory (Basque, Caucasian), as well as in the migratory families (Indo-European, Uralic, Turkic). Without doubt, we should reconstruct farming and pastoralism as systems that were inherent for at least Indo-European, Basque, and Caucasian families. There are several reasons for this. Beginning with Indo-European, a difference in the reliability of reconstructions

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Figure 58: The spaces of evolutionary behavior of farming vocabularies, representing 1. the in-door & small-scale farming space of the household and the family, generally characterized by low borrowability, low semantic instability, and wide-spread geographical homoplasy; 2. the out-door & large-scale farming space, characterized by medium borrowability, semantic instability, and higher geographical diversity; 3. the technology & war space, characterized by high and variating borrowability, semantic instability, and higher geographical diversity; and the wilderness space, characterized by highly variating levels of borrowability and semantic instability.

between lexemes for farming and pastoralism for the proto-language cannot be proven. Most of the lexemes of our data, with some exceptions, can safely be reconstructed to the Indo-European proto-language. This goes for the terminology of grains and cattle as well as for draft animals (e.g., horse) and vehicles. The precise form and function of these reconstructed artifacts in a past reality may remain obscure; possibly, a ‘wheel’ designated first the wheel of a spindle or a millstone and later the wheel of a chart (Heggarty 2014). We notice interesting parallelisms between Indo-European and Caucasian families here. A ‘wheel’ is in both families ‘the rotating [object]’, e.g., Proto-Kartvelian *borbal- ‘wheel’, Proto-Nakh and Proto-Dagestanian *bor-a ‘wheel, mills wheel’, from a root *bor- ‘to turn’; Proto-Indo-European *kʷekʷlo- ‘wheel’, from a root *kʷel- ‘to turn, rotate’. Second, the general degree of attested borrowability for our culture vocabulary in these families is low, for Indo-European around 10 %, for Caucasian 5 % (note that Caucasian has lower coverage in etymology). There is a distinct amount of ancient migration words in both languages, for some of which the exact details in reconstruction remain unclear. In Uralic, the degree of borrowability for the vocabulary is much higher, around 40 %, which reflects that the farming terminology, together with farming as a system, was borrowed and introduced secondarily to this family. This reflects the general view on these matters in the literature (Häkkinen 2001). However, can our data contribute to homeland theories, the dating of proto-languages, and directions or reconstructions of language migrations in prehistory? Homeland theories, together with proto-language chronologies, of the migratory families (Indo-European, Uralic) has been a matter of debate for more than a century (Hirt 1905, Schrader 1917, Gamkrelidze and Ivanov 1984, Anthony 2007, Haak et al. 2015, Mallory and Adams 2006). We would naturally like to contribute to the exploration of this enigma, and our data unveils some interesting patterns of prolonged language contact, which we assume are of importance to these questions. We believe, at first, that the Indo-Europeans were farmers, which is evident from the reconstructed vocabulary as well as the change behavior of the vocabulary during pre-historical and historical periods. It is not necessary that migratory languages such as Indo-European or Uralic, must have spread by quickly evolving ‘bottle-necks’, i.e., from a restricted area where, at a certain point in history, an enormous population expanse has spread a family over large parts of the Eurasian landmass. Rather, the Indo-European proto-language, like the Uralic proto-language, could have occupied a more extended area, in both space and time, something that would make a precise spatial reconstruction more difficult. The Yamna theory, the leading theory of

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contemporary comparative linguistics (Anthony 2007), which is also supported by evidence from ancient DNA (Haak et al. 2015) is currently the most likely theory of Indo-European origins, but in some aspects, the Yamna theory does not match reconstructed linguistic data (Mallory 2013). On the one side we have the huge area and the high diversity of the Indo-European family, the high certainty of reconstruction of farming vocabulary, the presence of ancient migration words shared with both Semitic and Caucasian languages, and the peripheral position of the Yamna area (roughly contemporary Ukraine) in terms of linguistic diversity and contact. On the other side we have the evidence by genetics, archaeology, and the arguments of etymologies in Greek and Germanic that cannot be reconstructed and are likely to be substrate. Genetics, like archaeological data, is very difficult to connect to populations of languages of the past. The evidence of language and culture, together with areal evidence amassed from thousand of years of documented change weighs heavier (cf. Klejn et al. 2017). Putting our grammatical and lexical evidence together and considering the areal patterns of features, both individually, in classes, and together, we may identify a number of distinct areal zones, which are characterized by specific behavior in terms of mutual contact and change (map 58). The first most striking tendency, falling out both from our lexical and grammatical data, is the division of our area into two regions; one eastern and one western. Even though Indo-European language family splits between the two regions, there are differences also among the Indo-European languages in our data that point in the direction of two disparate zones. First, the tendency is visible in grammar data, where the eastern and western region languages cluster with each other (see 5.9). The flow patterns of loans of culture words show a similar tendency: eastern languages are more frequently in mutual contact with each other, western region languages with each other (see 6.13). Apart from that, we may identify a number of distinct areas, which can be defined by their development, their level of impact upon other languages by language contact, as well as their general geographic position (map 58). First, we identify the Central Asian migration zone (map 58, 1), stretching from Mongolia to Eastern Europe and Caucasus, in grammar characterized by a widespread agglutinating tendency. In a later phase (2000–500 BP), the area is characterized by a large impact from Turkic and Arabic languages in terms of language contact (map 57). This is mainly the area of the migration of Turkic languages. In an earlier phase, around 4000– 2000 BP, the area constituted a spread zone for Indo-Iranian languages, which were in contact with the adjacent Uralic languages to the north. Second, we have the South Asian development zone (map 58, 2). Even though our lexical data from this area is scarcer, we can identify a South Asian zone (in our data mainly of Indo-European languages), typically characterized by deviating patterns in the vocabulary, as well as a special development of grammar patterns (map 27). Even though not reflected in our data, we assume that the Dravidian component is substantial in this zone. Next comes the West Asian contact zone (map 58, 3). This area, including Anatolia and West Asia, is characterized by very ancient written sources. The zone is, already in antiquity, characterized by high linguistic diversity, many relic languages, a high level of language contact, and frequent substitution of language populations. This is also, during history, a source area of many crucial innovations in cultural systems (see 6.5, 6.6, 6.11). Between the Black and Caspian Sea, we have the Caucasian accretion zone (map 58, 4). This area, which is generally characterized by a favorable climate, is an area of high linguistic diversity and independence, inhabited by the non-migratory Caucasian families. The high diversity and slow rate of change is evident from all data, both grammar and lexicon. The history of the spread of farming during the Neolithic and Chalcolithic periods indicates early contacts with the West Asian contact zone (6.5, 6.6), from where all cultural innovations must have been imported; yet there are few evident traces of early borrowing in the Caucasian families: most culture words have independent, inherited forms. In a later phase, there is a considerable impact from the Central Asian zone, through lexical borrowing from Turkic (map 57). In our vocabulary data, we see that the three families of Caucasus, Kartvelian, Nakh-Dagestanian, and Northwest Caucasian, form a unity of frequent

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shared cognacy. However, in terms of early language contact, these families are relatively independent in relation to the other families (Indo-European, Uralic). Numerous independent and inherited terms in Caucasian families for core culture lexemes, such as wheel or plow, indicate an independency. Moving to the east, we have the Eastern European periphery (map 58, 5). This area is characterized by a generally lower diversity (also taking into account that a many Uralic languages are absent in our data), and a tendency to diverge, in grammar and vocabulary, between the eastern and the western regions. We notice that the area, which in our data is mainly occupied by the Balto-Slavic languages, often forms a block with (Northern) European languages, but, in general (both grammar and vocabulary), the area is mainly characterized by conservatism. This is evident among others from the cluster analysis of grammar data (map 27, fig. 6). For this reason, we label the area “periphery” rather than “development zone”. In addition, borrowings are rather in the direction to the area than from the area (map 57). Our next area is the South-Central European development area (map 58, 6). This area, which is concentrated to the central parts of the Mediterranean and continues up to northern Europe, is characterized by an intense language contact and high borrowability, mainly in a direction south-to-north, but also from time to time north-to-south as well as central to east and west (map 57). In grammar, we notice a far-gone stage of development and areal convergence, visible at both individual and general levels (map 27, fig. 6). North of this we have the Northern European periphery (map 58, 7), mainly including northern parts of Scandinavia (7). This area is characterized by occurrence of local conservation zones and a general tendency (with some exceptions, such as Old Norse) of languages to be the target of loan rather than the source (map 57). Finally, we have the Atlantic periphery (map 58, 8), which also has, compared to the South-Central European development area, a more peripheral role, in that that languages are the target of borrowing rather than the source (map 57). The area also hosts the Basque accretion zone, an area of high linguistic conservatism. The aim of the current volume has been to investigate language change in time and space by means of salient grammatical and lexical change in a number of languages over a cohesive

Map 58: Overview of the sketched development areas, accretion zones and peripheries of the macro-area of our corpus. 1 = Central Asian migration zone, 2 = South Asian development zone, 3 = West Asian contact zone, 4 = Caucasian accretion zone, 5 = Eastern European periphery, 6 = South-Central European development area, 7 = Northern European periphery, 8 = Atlantic periphery.

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linguistic macro-area. The results give both a unified as well as a divergent picture, which is a good thing. In the introduction of this volume, we describe our theoretical framework where we see language as a complex, dynamic organism, in which change is divergent down to the most detailed level. The data confirms the theory – at least in principle. There are also astonishing exceptions, such as the occurrence, both in grammar and lexicon, of wide-spread geographic homoplasy, which even has the capacity to transgress the boundaries of total mutual unintelligibility, i.e., to erase the boundaries between highly remote families. Likewise, there are features that over time seem to be in a frequent, recurring state of divergent change: they seem never to subdue to conflation or convergence. To sum up; the current atlas has selected ~35 grammatical features (~120 variants) and ~100 lexical concepts that we have considered to be of continued importance in a Eurasian context and from a deep historical perspective. We have looked carefully at all the change processes of these selected features over a distinct macro-area, from the earliest sources and up to present day. Even though there are clear patterns in the data, the picture is highly dynamic and often blurred. Language change is a complex issue, which is entirely intertwined with cultural and environmental change. In addition, ~35 grammatical features and ~100 lexical concepts represent only a fraction of a complete language, which is far more complex than that. Therefore, we are fully aware that the change histories of other features may indicate other tendencies than what we have demonstrated here. That remains an issue for further investigation.

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Appendix 1: Languages of the current atlas (Language Name [a–z]; Latitude; Longitude; ISO Code; Subbranch).

Abaza; 41.12°N; 42.73°E; abq; Northwest Caucasian Abkhaz; 43°N; 41.02°E; abk; Northwest Caucasian Adyghe; 43.97°N; 39.29°E; ady; Northwest Caucasian Aghul; 41.92°N; 47.58°E; agx; Nakh-Dagestanian Albanian (Tosk); 40.45°N; 19.99°E; als; Indo-European: Albanian Andi; 42.81°N; 46.29°E; ani; Nakh-Dagestanian Anglo-Norman; 52.73°N; 1.5°W; xno; Indo-European: Germanic Angloromani; 53.78°N; 2.36°W; rme; Indo-European: Indo-Aryan Ashkun; 35.26°N; 70.79°E; ask; Indo-European: Nuristani Assamese; 26.14°N; 91.79°E; asm; Indo-European: Indo-Aryan Avar; 41.7°N; 46.56°E; ava; Nakh-Dagestanian Avestan; 31.71°N; 55.95°E; ave; Indo-European: Iranian Azerbaijani; 40.98°N; 46.47°E; azj; Turkic Baluchi; 26.28°N; 65.04°E; bal; Indo-European: Iranian Basque (East); 43.4°N; 1.45°W; baq; Basque Basque (West); 42.86°N; 2.68°W; baq; Basque Batsbi; 41.86°N; 45.65°E; bbl; Nakh-Dagestanian Belorussian; 53.23°N; 25.6°E; ; Indo-European: BaltoSlavic Bengali; 23.78°N; 90.28°E; ben; Indo-European: Indo-Aryan Beshta; 42.91°N; 44.08°E; kap; Nakh-Dagestanian Breton; 48°N; 4.1°W; bre; Indo-European: Celtic Buddhist Hybrid Sanskrit; 23.51°N; 76.29°E; ; IndoEuropean: Indo-Aryan Budukh; 41.18°N; 48.37°E; bdk; Nakh-Dagestanian Bulgarian; 42.7°N; 23.35°E; bul; Indo-European: BaltoSlavic Catalan; 41.38°N; 2.18°E; cat; Indo-European: Italic Celtiberian; 41.51°N; 1.02°W; xce; Indo-European: Celtic Chechen; 43.32°N; 45.69°E; che; Nakh-Dagestanian Classical Armenian; 39.94°N; 44.54°E; xcl; IndoEuropean: Armenian Classical Greek; 37.7°N; 24°E; grc; Indo-European: Greek Cornish; 50.19°N; 5.57°W; cor; Indo-European: Celtic Crimean Tatar; 45°N; 34.08°E; crh; Turkic Croatian; 45.81°N; 15.99°E; hrv; Indo-European: BaltoSlavic Czech; 50.07°N; 14.47°E; cze; Indo-European: BaltoSlavic Danish; 55.68°N; 12.58°E; dan; Indo-European: Germanic Dargwa; 42.43°N; 47.44°E; dar; Nakh-Dagestanian Dutch; 52.37°N; 4.9°E; nld; Indo-European: Germanic https://doi.org/10.1515/9783110367416-009

Elfdalian; 61.23°N; 14.04°E; ovd; Indo-European: Germanic English; 51.5°N; 0.1°W; eng; Indo-European: Germanic Estonian; 59.44°N; 24.75°E; est; Uralic Faroese; 62.01°N; 6.77°W; fao; Indo-European: Germanic Finnish; 60.17°N; 24.94°E; fin; Uralic French; 48.85°N; 2.35°E; fre; Indo-European: Italic Frisian; 53.2°N; 5.8°E; fry; Indo-European: Germanic Friulian; 46.13°N; 13.49°E; fur; Indo-European: Italic Gagauz; 44.6°N; 28.03°E; gag; Turkic Gaulish; 43.97°N; 3.19°E; xtg; Indo-European: Celtic Georgian; 41.62°N; 44.82°E; geo; Kartvelian German; 52.52°N; 13.41°E; ger; Indo-European: Germanic Gilaki; 37.53°N; 49.28°E; glk; Indo-European: Iranian Gothic; 53.04°N; 20.2°E; got; Indo-European: Germanic Gujarati; 22.44°N; 72.14°E; guj; Indo-European: Indo-Aryan Hindi; 28.63°N; 77.22°E; hin; Indo-European: Indo-Aryan Hittite; 40.01°N; 34.62°E; hit; Indo-European: Anatolian Hungarian; 47.5°N; 19.04°E; hun; Uralic Icelandic; 64.14°N; 21.94°W; ice; Indo-European: Germanic Ingush; 42.91°N; 44.08°E; inh; Nakh-Dagestanian Irish; 53.24°N; 9.3°W; gle; Indo-European: Celtic Italian; 43.12°N; 12.39°E; ita; Indo-European: Italic Kabardian; 43.37°N; 43.66°E; kbd; Northwest Caucasian Karachay-Balkar; 43.46°N; 41.21°E; krc; Turkic Kashmiri; 34.32°N; 75.94°E; kas; Indo-European: Indo-Aryan Kati; 35.8°N; 71.31°E; bsh; Indo-European: Nuristani Kazakh; 51.16°N; 71.46°E; kaz; Turkic Khinalug; 41.18°N; 48.13°E; kjj; Nakh-Dagestanian Khotanese; 38.33°N; 79.04°E; kho; Indo-European: Iranian Khowar; 36.46°N; 72.52°E; khw; Indo-European: Indo-Aryan Khwarshi; 42.32°N; 46.06°E; khv; Nakh-Dagestanian Konkani; 19.26°N; 72.87°E; knn; Indo-European: Indo-Aryan Kryz; 41.11°N; 48.09°E; kry; Nakh-Dagestanian Kumauni; 29.96°N; 80.03°E; kfy; Indo-European: Indo-Aryan Kumyk; 43°N; 47°E; kum; Turkic

402

Appendix 1: Languages of the current atlas

Kurdish (Kurmanji); 37.79°N; 43.82°E; kmr; IndoEuropean: Iranian Kurdish (Sorani); 35.82°N; 45.73°E; ckb; IndoEuropean: Iranian

Modern Armenian; 40.15°N; 44.53°E; arm; IndoEuropean: Armenian Modern Greek; 38.03°N; 23.69°E; gre; Indo-European: Greek

Ladin; 46.66°N; 11.92°E; lld; Indo-European: Italic Lahnda; 30.05°N; 72.51°E; lah; Indo-European: Indo-Aryan Lak; 42.13°N; 47.08°E; lbe; Nakh-Dagestanian Late Latin; 42.26°N; 12.56°E; ; Indo-European: Italic Latin; 41.89°N; 12.49°E; lat; Indo-European: Italic Latvian; 56.92°N; 24.11°E; lav; Indo-European: BaltoSlavic Laz; 41.46°N; 41.57°E; lzz; Kartvelian Lezgian; 41.55°N; 48.04°E; lez; Nakh-Dagestanian Lithuanian; 54.68°N; 25.26°E; lit; Indo-European: Balto-Slavic Low German; 53.93°N; 9.49°E; nds; Indo-European: Germanic Luwian; 36.62°N; 36.79°E; xlu; Indo-European: Anatolian Lycian; 36.36°N; 29.32°E; xlc; Indo-European: Anatolian Lydian; 38.49°N; 28.04°E; xld; Indo-European: Anatolian

Nepali; 26.66°N; 89.24°E; npi; Indo-European: Indo-Aryan Northern Saami; 69.42°N; 20.27°E; sme; Uralic Norwegian; 59.91°N; 10.74°E; nor; Indo-European: Germanic Norwegian (Bokmål); 59.91°N; 10.74°E; nob; IndoEuropean: Germanic Norwegian (Nynorsk); 60.33°N; 5.08°E; nno; IndoEuropean: Germanic

Maithili; 26.08°N; 86.16°E; mai; Indo-European: Indo-Aryan Maldivian; 4.17°N; 73.51°E; div; Indo-European: Indo-Aryan Manx; 54.15°N; 4.48°W; glv; Indo-European: Celtic Marathi; 19.39°N; 75.49°E; mar; Indo-European: Indo-Aryan Marwari; 26.47°N; 70.02°E; mve; Indo-European: Indo-Aryan Medieval Latin; 42.56°N; 12.62°E; ; Indo-European: Italic Megrelian; 42.37°N; 41.94°E; xmf; Kartvelian Middle Breton; 47.21°N; 1.53°W; xbm; Indo-European: Celtic Middle Cornish; 50.1°N; 5.21°W; cnx; Indo-European: Celtic Middle Dutch; 52.21°N; 5.96°E; dum; Indo-European: Germanic Middle English; 51.31°N; 0.76°W; enm; Indo-European: Germanic Middle French; 48.85°N; 2.35°E; frm; Indo-European: Italic Middle Greek; 41.06°N; 29°E; grc; Indo-European: Greek Middle High German; 48.74°N; 9.72°E; gmh; IndoEuropean: Germanic Middle Irish; 52.66°N; 8.63°W; mga; Indo-European: Celtic Middle Low German; 53.87°N; 10.69°E; gml; IndoEuropean: Germanic Middle Persian; 32.65°N; 51.68°E; pal; Indo-European: Iranian Middle Welsh; 52.24°N; 3.38°W; wlm; Indo-European: Celtic

Occitan; 43.75°N; 2.51°E; oci; Indo-European: Italic Old Awadhi; 26.85°N; 80.96°E; ; Indo-European: Indo-Aryan Old Breton; 47.66°N; 2.76°W; obt; Indo-European: Celtic Old Church Slavonic; 43.96°N; 22.87°E; chu; IndoEuropean: Balto-Slavic Old Cornish; 50.26°N; 5.05°W; oco; Indo-European: Celtic Old Czech; 50.07°N; 14.47°E; ; Indo-European: BaltoSlavic Old Danish; 55.68°N; 12.58°E; ; Indo-European: Germanic Old Dutch; 52.09°N; 5.12°E; odt; Indo-European: Germanic Old English; 51.06°N; 1.31°W; ang; Indo-European: Germanic Old Franconian; 52.9°N; 9.98°E; frk; Indo-European: Germanic Old French; 48.85°N; 2.35°E; fro; Indo-European: Italic Old Frisian; 53.22°N; 6.57°E; ofs; Indo-European: Germanic Old Georgian; 41.84°N; 44.71°E; oge; Kartvelian Old Gujarati; 22.44°N; 72.14°E; ; Indo-European: Indo-Aryan Old High German; 49.8°N; 9.96°E; goh; IndoEuropean: Germanic Old Irish; 53.73°N; 6.87°W; sga; Indo-European: Celtic Old Italian; 43.78°N; 11.25°E; ; Indo-European: Italic Old Marathi; 19.39°N; 75.49°E; ; Indo-European: Indo-Aryan Old Norse; 63.43°N; 10.4°E; non; Indo-European: Germanic Old Persian; 29.94°N; 52.89°E; peo; Indo-European: Iranian Old Portuguese; 41.16°N; 8.63°W; ; Indo-European: Italic Old Provençal; 43.43°N; 6.22°E; pro; Indo-European: Italic Old Prussian; 54.44°N; 19.9°E; prg; Indo-European: Balto-Slavic Old Russian; 58.52°N; 31.28°E; orv; Indo-European: Balto-Slavic Old Saxon; 53.08°N; 8.81°E; osx; Indo-European: Germanic

Appendix 1: Languages of the current atlas

Old Spanish; 42.39°N; 3.89°W; osp; Indo-European: Italic Old Swedish; 58.48°N; 16.32°E; ; Indo-European: Germanic Old Testament Hebrew; 31.77°N; 35.22°E; hbo; Semitic Old Welsh; 52.59°N; 4.09°W; owl; Indo-European: Celtic Oriya; 20.61°N; 86.28°E; ory; Indo-European: Indo-Aryan Oscan; 41.07°N; 15.15°E; osc; Indo-European: Italic Ossetian (Iron); 43.04°N; 44.68°E; oss; IndoEuropean: Iranian Pali; 27.62°N; 83°E; pli; Indo-European: Indo-Aryan Parachi; 34.83°N; 69.7°E; prc; Indo-European: Iranian Pashto; 31.43°N; 68.19°E; pus; Indo-European: Iranian Persian; 32.74°N; 55.75°E; per; Indo-European: Iranian Polish; 52.24°N; 20.99°E; pol; Indo-European: BaltoSlavic Portuguese; 38.71°N; 9.14°W; por; Indo-European: Italic Prakrit; 25.38°N; 84.73°E; pra; Indo-European: Indo-Aryan Prasun; 35.34°N; 70.74°E; prn; Indo-European: Nuristani Provençal; 43.43°N; 6.22°E; oci; Indo-European: Italic Punjabi; 31.54°N; 74.35°E; pan; Indo-European: Indo-Aryan Romani (Arli); 42.97°N; 19.88°E; rmn; Indo-European: Indo-Aryan Romani (Banatiski Gurbet); 45.6°N; 20.26°E; ; IndoEuropean: Indo-Aryan Romani (Bugurdži); 42.12°N; 21.22°E; ; Indo-European: Indo-Aryan Romani (Burgenland); 47.19°N; 16.38°E; ; IndoEuropean: Indo-Aryan Romani (Crimean); 43.59°N; 40.19°E; ; Indo-European: Indo-Aryan Romani (Dolenjski); 45.96°N; 14.04°E; ; IndoEuropean: Indo-Aryan Romani (East Slovak); 49.76°N; 15.26°E; ; IndoEuropean: Indo-Aryan Romani (Gurbet); 43.78°N; 19.22°E; ; Indo-European: Indo-Aryan Romani (Gurvari); 47.04°N; 20.06°E; ; Indo-European: Indo-Aryan Romani (Hungarian Vend); 46.23°N; 17.2°E; ; IndoEuropean: Indo-Aryan Romani (Kale); 60.97°N; 21.47°E; rmf; Indo-European: Indo-Aryan Romani (Kelderash); 47.19°N; 22.5°E; rmy; IndoEuropean: Indo-Aryan Romani (Kosovo Arli); 42.52°N; 20.96°E; rmn; IndoEuropean: Indo-Aryan Romani (Latvian); 56.31°N; 24.34°E; ; Indo-European: Indo-Aryan Romani (Lithuanian); 55.07°N; 22.08°E; ; IndoEuropean: Indo-Aryan Romani (Lovara); 47.4°N; 23.09°E; rmy; Indo-European: Indo-Aryan

403

Romani (Macedonian Arli); 41.99°N; 21.45°E; rmn; Indo-European: Indo-Aryan Romani (Macedonian Džambazi); 42.13°N; 21.72°E; ; Indo-European: Indo-Aryan Romani (North Russian); 54°N; 32.36°E; ; IndoEuropean: Indo-Aryan Romani (Prekmurski); 46.13°N; 15.36°E; ; IndoEuropean: Indo-Aryan Romani (Romungro); 47.93°N; 18.55°E; rmc; IndoEuropean: Indo-Aryan Romani (Sepečides); 38.39°N; 27.13°E; ; IndoEuropean: Indo-Aryan Romani (Sinte); 51.5°N; 10.2°E; rmo; Indo-European: Indo-Aryan Romani (Sofia Erli); 42.7°N; 23.33°E; rmn; IndoEuropean: Indo-Aryan Romani (Sremski Gurbet); 45.59°N; 19.85°E; ; IndoEuropean: Indo-Aryan Romani (Ursari); 46.09°N; 24.59°E; ; Indo-European: Indo-Aryan Romani (Veršend); 46.35°N; 19.73°E; ; Indo-European: Indo-Aryan Romani (Welsh); 52.03°N; 3.6°W; rmw; Indo-European: Indo-Aryan Romanian; 44.43°N; 26.09°E; rum; Indo-European: Italic Romansh; 46.5°N; 9.84°E; roh; Indo-European: Italic Russian; 55.68°N; 37.65°E; rus; Indo-European: BaltoSlavic Rutul; 41.62°N; 47.32°E; rut; Nakh-Dagestanian Sanskrit; 23.51°N; 76.29°E; san; Indo-European: Indo-Aryan Sardinian; 40.32°N; 9.33°E; srd; Indo-European: Italic Scandoromani; 59.48°N; 13.16°E; rmu; Indo-European: Indo-Aryan Scottish Gaelic; 57.16°N; 7.37°W; gla; Indo-European: Celtic Scythian; 50.09°N; 37.29°E; xsc; Indo-European: Iranian Serbian; 44.8°N; 20.47°E; srp; Indo-European: BaltoSlavic Serbo-Croatian; 45.3°N; 17.99°E; ; Indo-European: Balto-Slavic Shughni; 38.39°N; 71.5°E; sgh; Indo-European: Iranian Sicilian; 38.12°N; 13.37°E; scn; Indo-European: Italic Sindhi; 23.25°N; 69.67°E; snd; Indo-European: Indo-Aryan Sinhalese; 6.94°N; 79.86°E; sin; Indo-European: Indo-Aryan Slovakian; 48.55°N; 18.78°E; ; Indo-European: BaltoSlavic Slovene; 46.05°N; 14.51°E; slv; Indo-European: BaltoSlavic Sogdian; 39.65°N; 66.96°E; sog; Indo-European: Iranian Southern Altai; 50.13°N; 86.87°E; alt; Turkic Spanish; 40.42°N; 3.7°W; spa; Indo-European: Italic Standard Arabic; 27°N; 43°E; arb; Semitic Svan; 42.99°N; 42.52°E; sva; Kartvelian

404

Appendix 1: Languages of the current atlas

Swedish; 59.74°N; 17.44°E; swe; Indo-European: Germanic Swiss German; 47.37°N; 8.54°E; gsw; Indo-European: Germanic Syriac; 37.15°N; 38.82°E; syc; Semitic Tabasaran; 42.02°N; 47.84°E; tab; Nakh-Dagestanian Tajik; 38.66°N; 70.34°E; tgk; Indo-European: Iranian Talysh; 38.85°N; 48.73°E; tly; Indo-European: Iranian Thracian; 42.06°N; 22.15°E; txh; Indo-European: unclassified Tocharian A; 41.76°N; 86.15°E; xto; Indo-European: Tocharian Tocharian B; 41.65°N; 81.51°E; txb; Indo-European: Tocharian Tregami; 34.95°N; 71.04°E; trm; Indo-European: Nuristani Tsakhur; 41.59°N; 46.89°E; tkr; Nakh-Dagestanian Turkish; 39.93°N; 32.86°E; tur; Turkic Turkmen; 37.94°N; 58.39°E; tuk; Turkic Tuvan; 48.44°N; 92.67°E; tyv; Turkic Ubykh; 43.67°N; 39.67°E; uby; Northwest Caucasian Udi; 42.91°N; 44.08°E; udi; Nakh-Dagestanian

Ugaritic; 35.61°N; 35.79°E; uga; Semitic Ukrainian; 50.45°N; 30.53°E; ukr; Indo-European: Balto-Slavic Umbrian; 43.35°N; 12.59°E; xum; Indo-European: Italic Upper Sorbian; 51.18°N; 14.43°E; hsb; Indo-European: Balto-Slavic Urdu; 33.68°N; 73.02°E; urd; Indo-European: Indo-Aryan Uyghur; 43.83°N; 87.6°E; uig; Turkic Uzbek; 41.3°N; 69.26°E; uzb; Turkic Vulgar Latin; 42.56°N; 12.62°E; ; Indo-European: Italic Waigali; 35.09°N; 70.93°E; wbk; Indo-European: Nuristani Wakhi; 37.22°N; 72.76°E; wbl; Indo-European: Iranian Walloon; 50.46°N; 4.87°E; wln; Indo-European: Italic Welsh; 52.93°N; 4.39°W; wel; Indo-European: Celtic Yagnobi; 39.38°N; 69.05°E; yai; Indo-European: Iranian Yiddish; 49.85°N; 24.03°E; ydd; Indo-European: Germanic

Appendix 2a: Grammar: Features, complete list (from DiACL) This appendix gives the complete list of Grids, Features, and Variants, extracted from the database DiACL. Data is given in the following order: GRID (Name of the main domain); FEATURE (Name of the Feature); FEATURE: DESCRIPTION (Description of the Feature in accordance with the questionnaire of the database); VARIANT (Name of the Variant); VARIANT: DESCRIPTION (Description of the Variant in accordance with the questionnaire of the database); VARIANT ID 213–330 (ID number of the Variant from the database DiACL).

Word order; Adpositions; Do adpositions normally occur before or after the noun?; Prep; Does the language have a substantial set of prepositions? E.g. English in the house; 213 Word order; Adpositions; Do adpositions normally occur before or after the noun?; Post; Does the language have a substantial set of postpositions?; 214 Word order; Noun-adjective; Do adjectives normally occur before or after the noun?; NA; Do most adjectives occur after the noun?; 215 Word order; Noun-adjective; Do adjectives normally occur before or after the noun?; AN; Do most adjectives occur before the noun?; 216 Word order; Noun-relative clause; Do relative clauses normally occur before or after the noun?; NRel; Do most relative clauses occur after the noun?; 217 Word order; Noun-relative clause; Do relative clauses normally occur before or after the noun?; RelN; Do most relative clauses occur before the noun?; 218 Word order; Noun-possessor; Do possessors normally occur before or after the noun?; N-Poss; Do most possessors occur after the noun they possess? The possessor should be an animate noun, and neither a proper name nor a pronoun!; 219 Word order; Noun-possessor; Do possessors normally occur before or after the noun?; Poss-N; Do most possessors occur before the noun they possess? The possessor should be an animate noun, and neither a proper name nor a pronoun!; 220 Word order; WH-element; What is the position of the WH-question word?; WH-initial; Is the WHquestion word always obligatorily the first element in a question (e.g., it does not trigger inversion)?; 221 Word order; WH-element; What is the position of the WH-question word?; WH-V; Does the WH-question word always immediately precede the verb (i.e., stand directly before the verb, either initially or non-initially)?; 222 Word order; Main clause; What is the canonical (neutral) word order in a main clause?; SVO; What is the canonical (neutral) word order in a main clause? NB: V2 languages like Swe and Ger do NOT count as SVO even though SVO is most frequent.; 223 Word order; Main clause; What is the canonical (neutral) word order in a main clause?; V2; V2 implies that initial adverb triggers V-SUBJ word order (Swedish, German etc.).; 224 https://doi.org/10.1515/9783110367416-010

Word order; Main clause; What is the canonical (neutral) word order in a main clause?; VSO; What is the canonical (neutral) word order in a main clause?; 225 Word order; Main clause; What is the canonical (neutral) word order in a main clause?; SOV; What is the canonical (neutral) word order in a main clause?; 226 Word order; Subordinate clause; What is the canonical (neutral) word order in a subordinate clause?; SVO; What is the canonical (neutral) word order in a subordinate clause? NB: V2 languages like Swe and Ger do NOT count as SVO even though SVO is most frequent.; 227 Word order; Subordinate clause; What is the canonical (neutral) word order in a subordinate clause?; V2; V2 implies that initial adverb triggers V-SUBJ word order (Swedish, German etc.).; 228 Word order; Subordinate clause; What is the canonical (neutral) word order in a subordinate clause?; VSO; What is the canonical (neutral) word order in a subordinate clause?; 229 Word order; Subordinate clause; What is the canonical (neutral) word order in a subordinate clause?; SOV; What is the canonical (neutral) word order in a subordinate clause?; 230 Word order; Infinitive; Does the object normally occur before or after an infinitive? E.g.: to make pancakes (VO) Pfannkuchen machen (OV); VO; ; 231 Word order; Infinitive; Does the object normally occur before or after an infinitive? E.g.: to make pancakes (VO) Pfannkuchen machen (OV); OV; ; 232 Word order; Participle; Does the object normally occur before or after a participle? E.g.: making pancakes (VO) Pfannkuchen machend (OV); VO; ; 233 Word order; Participle; Does the object normally occur before or after a participle? E.g.: making pancakes (VO) Pfannkuchen machend (OV); OV; ; 234 Word order; Clitic pronouns finite verb; Does the clitic object pronoun normally occur before or after a finite verb? E.g.: Je les fais. (OV) If a language does not have clitic object pronouns, it would be 0 in both OV and VO.; VO; ; 235 Word order; Clitic pronouns finite verb; Does the clitic object pronoun normally occur before or after a

406

Appendix 2a: Grammar: Features, complete list (from DiACL)

finite verb? E.g.: Je les fais. (OV) If a language does not have clitic object pronouns, it would be 0 in both OV and VO.; OV; ; 236 Word order; Clitic pronouns finite verb; Does the clitic object pronoun normally occur before or after a finite verb? E.g.: Je les fais. (OV) If a language does not have clitic object pronouns, it would be 0 in both OV and VO.; 2nd position; Does the clitic pronoun always occur in 2nd position, not specifically before or after the verb? (Wackernagel position); 237 Word order; Clitic pronouns infinitive; Does the clitic object pronoun normally occur before or after an infinitive? E.g.: Je veux les faire. (OV) If a language does not have clitic object pronouns, it would be 0 in both OV and VO.; VO; ; 238 Word order; Clitic pronouns infinitive; Does the clitic object pronoun normally occur before or after an infinitive? E.g.: Je veux les faire. (OV) If a language does not have clitic object pronouns, it would be 0 in both OV and VO.; OV; ; 239 Word order; Clitic pronouns infinitive; Does the clitic object pronoun normally occur before or after an infinitive? E.g.: Je veux les faire. (OV) If a language does not have clitic object pronouns, it would be 0 in both OV and VO.; 2nd position; Does the clitic pronoun always occur in 2nd position, not specifically before or after the verb?; 240 Word order; Clitic pronouns participle; Does the clitic object pronoun normally occur before or after a participle? E.g.: En les faisant… (OV) If a language does not have clitic object pronouns, it would be 0 in both OV and VO.; VO; ; 241 Word order; Clitic pronouns participle; Does the clitic object pronoun normally occur before or after a participle? E.g.: En les faisant … (OV) If a language does not have clitic object pronouns, it would be 0 in both OV and VO.; OV; ; 242 Word order; Clitic pronouns participle; Does the clitic object pronoun normally occur before or after a participle? E.g.: En les faisant … (OV) If a language does not have clitic object pronouns, it would be 0 in both OV and VO.; 2nd position; Does the clitic pronoun always occur in 2nd position, not specifically before or after the verb?; 243 Nominal morphology; Nominal case; What is the realization of case at nouns (nominal heads)?; O-case; Are there different noun forms for agent and object case? (English: 0 (no cases) Russian: 1 (different noun forms for accusative and nominative) Basque: 1 (different noun forms for ergative and absolutive); 244 Nominal morphology; Nominal case; What is the realization of case at nouns (nominal heads)?; DAT; Is there a specific case form for the recipient, which is different from the case form of, e.g., the object? (E.g. The man gives a book (O) to the child (DAT)); 245 Nominal morphology; Nominal case; What is the realization of case at nouns (nominal heads)?;

GEN; Is there a special case form to express genitive, which is different from the agent/object case?; 246 Nominal morphology; Nominal case; What is the realization of case at nouns (nominal heads)?; GEN/DAT; Is there a special noun form to express genitive, which is not the same as dative (recipient) case?; 247 Nominal morphology; Nominal case; What is the realization of case at nouns (nominal heads)?; VOC; Is there a special noun form to express vocative which is not the same as agent or object case?; 248 Nominal morphology; Nominal case; What is the realization of case at nouns (nominal heads)?; OBL-Cases; Are there any cases besides agent, object, genitive, dative, and vocative? (E.g., local cases); 249 Nominal morphology; Nominal case; What is the realization of case at nouns (nominal heads)?; > 7 Cases; Are there more than 7 cases?; 250 Nominal morphology; Nominal case; What is the realization of case at nouns (nominal heads)?; AGGL.CASE; Are there cases which are visibly agglutinative, i.e., built up by several distinct, segmentable affixes?; 251 Nominal morphology; Nominal case; What is the realization of case at nouns (nominal heads)?; AGGL.CASE.NR; Are plural cases formed by combining an (infixed) plural affix and a case affix in an agglutinative manner?; 252 Nominal morphology; Pronominal case; What is the realization of case at pronouns (pronominal heads)? Mainly 1st and 2nd person pronouns, ignoring 3rd person pronouns (which often come from demonstratives).; A ≠ O; In pronouns, is the marking different for the case of the agent and object?; 253 Nominal morphology; Pronominal case; What is the realization of case at pronouns (pronominal heads)? Mainly 1st and 2nd person pronouns, ignoring 3rd person pronouns (which often come from demonstratives).; DAT ≠ O; In pronouns, is the marking different for the case of the recipient and the object?; 254 Nominal morphology; Pronominal case; What is the realization of case at pronouns (pronominal heads)? Mainly 1st and 2nd person pronouns, ignoring 3rd person pronouns (which often come from demonstratives).; VOC; See Nominal case; 255 Nominal morphology; Pronominal case; What is the realization of case at pronouns (pronominal heads)? Mainly 1st and 2nd person pronouns, ignoring 3rd person pronouns (which often come from demonstratives).; OBL-Cases; See Nominal case; 256 Nominal morphology; Pronominal case; What is the realization of case at pronouns (pronominal heads)? Mainly 1st and 2nd person pronouns, ignoring 3rd person pronouns (which often come

Appendix 2a: Grammar: Features, complete list (from DiACL)

from demonstratives).; > 7 Cases; See Nominal case; 257 Nominal morphology; Pronominal case; What is the realization of case at pronouns (pronominal heads)? Mainly 1st and 2nd person pronouns, ignoring 3rd person pronouns (which often come from demonstratives).; AGGL.CASE; See Nominal case; 258 Nominal morphology; Pronominal case; What is the realization of case at pronouns (pronominal heads)? Mainly 1st and 2nd person pronouns, ignoring 3rd person pronouns (which often come from demonstratives).; AGGL.CASE.NR; See Nominal case; 259 Nominal morphology; Case marking; On which elements of the NP is the case marking obligatory?; CASE-LAST; Is the case marking obligatory on the last element of the NP (i.e., it is only realized once in the NP, even if it consists of several elements)?; 260 Nominal morphology; Case marking; On which elements of the NP is the case marking obligatory?; CASE-FIRST; Is the case marking obligatory on the first element of the NP (i.e., it is only realized once in the NP, even if it consists of several elements)?; 261 Nominal morphology; Case marking; On which elements of the NP is the case marking obligatory?; CASE-N; Is the case marking obligatory realized on the noun?; 262 Nominal morphology; Case marking; On which elements of the NP is the case marking obligatory?; CASE-ADJ; Is the case marking obligatory on the adjective?; 263 Nominal morphology; Case marking; On which elements of the NP is the case marking obligatory?; CASE-ART; Is the case marking realized on the article?; 264 Nominal morphology; Gender / noun class; How is gender / noun class realized in the language?; M/F; Is there an obligatory gender distinction between masculine and feminine realized on an agreeing article or adjective? Can be either on the adjective (Russian) or on both the article and the adjective (German), or even on a verb (as in some NE Caucasian languages).; 265 Nominal morphology; Gender / noun class; How is gender / noun class realized in the language?; NEUTR; Is there a special neutral gender for nouns realized on an agreeing article, adjective or verb?; 266 Nominal morphology; Gender / noun class; How is gender / noun class realized in the language?; ANIM; Is there a special noun class for non-human animates realized on an agreeing article, adjective or verb?; 267 Nominal morphology; Gender / noun class; How is gender / noun class realized in the language?; < 5 GENDER; Are there more than 5 noun classes (or genders)?; 268

407

Nominal morphology; Definiteness marking; How is definiteness marking realized in the language?; DEF-ART; Is there a special word class of definite articles which occur in NPs without adjectives? (E.g.: German, English but not Swedish); 269 Nominal morphology; Definiteness marking; How is definiteness marking realized in the language?; NDEF; Is there a suffix for definiteness on the noun? (E.g.: Swedish but not English!); 270 Nominal morphology; Definiteness marking; How is definiteness marking realized in the language?; ADJ-DEF; Is there a suffix for definiteness on the adjective? This includes cases when the ADJ has a different form in definite and indefinite NPs (Swe “det stora huset”, Ger “das grosse Haus”).; 271 Nominal morphology; Definiteness marking; How is definiteness marking realized in the language?; DEF-LAST; Is the definiteness marking obligatory on the last element of the NP (so it is only realized once in the NP, even if it consists of several elements)? If there is no definiteness marking at all, it will be 0!; 272 Nominal morphology; Definiteness marking; How is definiteness marking realized in the language?; DEF-FIRST; Is the definiteness marking obligatory on the first element of the NP (so it is only realized once in the NP, even if it consists of several elements)? If there is no definiteness marking at all, it will be 0!; 273 Nominal morphology; Gender agreement; How is gender agreement realized in the language?; PRED-ADJ; Does a predicative adjective agree with the subject of the clause in gender?; 274 Nominal morphology; Preposition agreement; How is preposition agreement realized in the language?; PREP-PRON-AGR; Can a preposition agree in person with its object?; 275 Verbal morphology; Simple PAST, A; In simple past, how is verbal agreement realized with respect to the agent?; PST:A-AGR-FULL; In simple past: does the verb crossreference the agent in all persons / numbers?; 276 Verbal morphology; Simple PAST, A; In simple past, how is verbal agreement realized with respect to the agent?; PST:NO-A-AGR; In simple past: does the verb not crossreference the agent on the verb at all (e.g., Swedish)?; 277 Verbal morphology; Simple PAST, A; In simple past, how is verbal agreement realized with respect to the agent?; PST:A-Gender-AGR; In simple past, does the verb agree in gender with the subject of a transitive verb? (e.g., Russian, Polish).; 278 Verbal morphology; Simple PAST, O; In simple past, how is verbal agreement realized with respect to the object?; PST:O-AGR-FULL; In simple past: does the verb crossreference the object in all persons / numbers?; 279 Verbal morphology; Simple PAST, O; In simple past, how is verbal agreement realized with respect to the object?; PST:NO-O-AGR; In simple past: does

408

Appendix 2a: Grammar: Features, complete list (from DiACL)

the verb not crossreference the object on the verb at all (e.g., Swedish, English, Russian)?; 280 Verbal morphology; Simple PAST, O; In simple past, how is verbal agreement realized with respect to the object?; PST:O-Gender-AGR; In simple past, does the verb agree in gender with the object?; 281 Verbal morphology; Simple PAST, DAT; In simple past, how is verbal agreement realized with respect to the indirect object of ditransitive verbs?; PST:DATAGR-FULL; In simple past: does the verb crossreference the dative in all persons / numbers?; 282 Verbal morphology; Simple PAST, DAT; In simple past, how is verbal agreement realized with respect to the indirect object of ditransitive verbs?; PST:NO-DAT-AGR; In simple past: does the verb not crossreference the dative on the verb at all (e.g., Swedish, English, Russian); 283 Verbal morphology; Simple PAST, DAT; In simple past, how is verbal agreement realized with respect to the indirect object of ditransitive verbs?; PST:DATGender-AGR; In simple past, does the verb agree in gender with the indirect object of a ditransitive verb?; 284 Verbal morphology; Present progressive, A; In present progressive: how is verbal agreement realized with respect to the agent?; PROG:A-AGR-FULL; In present progressive: does the verb crossreference the agent in all persons /numbers?; 285 Verbal morphology; Present progressive, A; In present progressive: how is verbal agreement realized with respect to the agent?; PROG:NO-A-AGR; In present progressive: does the verb not crossreference the agent on the verb at all (e.g., Swedish); 286 Verbal morphology; Present progressive, A; In present progressive: how is verbal agreement realized with respect to the agent?; PROG:A-Gender-AGR; In present progressive, does the verb agree in gender with the subject of a transitive verb?; 287 Verbal morphology; Present progressive, O; In present progressive, how is verbal agreement organized with respect to the object?; PROG:O-AGR-FULL; In present progressive: does the verb crossreference the object in all persons /numbers?; 288 Verbal morphology; Present progressive, O; In present progressive, how is verbal agreement organized with respect to the object?; PROG:NO-O-AGR; In present progressive: does the verb not crossreference the object on the verb at all (e.g. Swedish, Russian)?; 289 Verbal morphology; Present progressive, O; In present progressive, how is verbal agreement organized with respect to the object?; PROG:O-Gender-AGR; In present progressive, does the verb agree in gender with the object of a transitive verb?; 290 Verbal morphology; Present progressive, DAT; In present progressive, how is verbal agreement organized with respect to the indirect object of ditransitive verbs?; PROG:DAT-AGR-FULL; Iin

present progressive: does the verb crossreference the indirect object of a ditransitive verb in all persons /numbers?; 291 Verbal morphology; Present progressive, DAT; In present progressive, how is verbal agreement organized with respect to the indirect object of ditransitive verbs?; PROG:NO-DAT-AGR; In present progressive: does the verb not crossreference the indirect object of ditransitive verbs at all (e.g. Swedish, English, Russian)?; 292 Verbal morphology; Present progressive, DAT; In present progressive, how is verbal agreement organized with respect to the indirect object of ditransitive verbs?; PROG:DAT-Gender-AGR; In the present progressive, does the verb agree in gender with the indirect object of a ditransitive verb?; 293 Verbal morphology; Allocutive agreement; Does the verb agree with the receiver (the person one is speaking to) without the speaker being an argument in the sentence (allocutive agreement, probably no for all languages but Basque!); ALLOC; Does the verb agree with the receiver (the person one is speaking to) without the speaker being an argument in the sentence (allocutive agreement, probably no for all languages but Basque!); 294 Tense; Future; How is future realized in the language?; FUT.AUX; Is there a future formed by an auxiliary? (E.g., will in English?); 295 Tense; Future; How is future realized in the language?; PERF.FUT; Is there a future formed by using the perfective aspect? (0 if the language does not have verbal aspects! E.g., Russian, Georgian); 296 Tense; Future; How is future realized in the language?; FUT.Participle; Is there a future formed by a participle? (E.g., Armenian, Basque); 297 Tense; Future; How is future realized in the language?; FUT.Particle; Is there a future formed by a particle preceding a finite verb? (E.g., Albanian); 298 Tense; Future; How is future realized in the language?; FUT.Synth; Is there a synthetical future? (E.g., French, Spanish); 299 Tense; Continous present; How is present progressive realized in the language?; Present; Is there a synthetic present in progressive function?; 300 Tense; Continous present; How is present progressive realized in the language?; Progressive present; Is there a progressive present form constructed by combining a present participle with a finite auxiliary verb?; 301 Alignment; Noun: Simple Past; In simple past: how is the marking of subject and object of nouns realized?; N:PST:A=O?; In simple past: Is the noun form for A the same as for O? Ie: Does the noun look the same when it is subject of a transitive clause than when it is object of a transitive clause?; 302 Alignment; Noun: Simple Past; In simple past: how is the marking of subject and object of nouns realized?; N:PST:A=Sa?; In simple past:Is the noun

Appendix 2a: Grammar: Features, complete list (from DiACL)

form for A the same as for Sa? Ie: Does the noun look the same when it is subject of a transitive clause as when it is subject of an agentive intransitive verb such as “work” or “dance”?; 303 Alignment; Noun: Simple Past; In simple past: how is the marking of subject and object of nouns realized?; N:PST: O=So?; In simple past: Is the noun form for O the same as for So? Ie: Does the noun look the same when it is object of a transitive clause as when it is subject of an unaccusative verb such as “fall” or “die”?; 304 Alignment; Noun: Simple Past; In simple past: how is the marking of subject and object of nouns realized?; N:PST:Sa=So?; In simple past: Does a noun bear the same case form when it is Sa (subject of e.g. work) or So (subject of e.g. fall or die)? Ie: There does not exist a split into stative and active intransitive verbs.; 305 Alignment; Noun: Present Progressive; In present progressive: how is the marking of subject and object of nouns realized?; N:PROG:A=O?; In present progressive: Is the noun form for A the same as for O? I.e.: Does the noun look the same when it is subject of a transitive clause and when it is object of a transitive clause?; 306 Alignment; Noun: Present Progressive; In present progressive: how is the marking of subject and object of nouns realized?; N:PROG:A=Sa?; In present progressive:Is the noun form for A the same as for Sa? I.e.: Does the noun look the same when it is subject of a transitive clause and when it is subject of an agentive intransitive verb such as “work” or “dance”?; 307 Alignment; Noun: Present Progressive; In present progressive: how is the marking of subject and object of nouns realized?; N:PROG:O=So?; In present progressive: Is the noun form for O the same as for So? I.e.: Does the noun look the same when it is object of a transitive clause and when it is subject of an unaccusative verb such as “fall” or “die”?; 308 Alignment; Noun: Present Progressive; In present progressive: how is the marking of subject and object of nouns realized?; N:PROG:Sa=So?; In present progressive: does a noun bear the same case form when it is Sa (subject of e.g., “work”) or So (subject of e.g., “fall” or “die”)? I.e.: The language does not have a split between stative and active intransitive verbs.; 309 Alignment; Pronoun: Simple Past; In present progressive: how is the marking of subject and object of pronouns realized?; P:PST:A=O?; In simple past: Is the pronoun form for A the same as for O? I.e.: Does the pronoun look the same when it is subject of a transitive clause than when it is object of a transitive clause?; 310 Alignment; Pronoun: Simple Past; In present progressive: how is the marking of subject and object of pronouns realized?; P:PST:A=Sa?; In simple past: Is the pronoun form for A the same as for Sa? I.e.: Does the pronoun look the same

409

when it is subject of a transitive clause than when it is subject of an agentive intransitive verb such as “work” or “dance”?; 311 Alignment; Pronoun: Simple Past; In present progressive: how is the marking of subject and object of pronouns realized?; P:PST: O=So?; In simple past: Is the pronoun form for O the same as for So? I.e.: Does the pronoun look the same when it is object of a transitive clause than when it is subject of an unaccusative verb such as “fall” or “die”?; 312 Alignment; Pronoun: Simple Past; In present progressive: how is the marking of subject and object of pronouns realized?; P:PST:Sa=So?; In simple past: Does the pronoun bear the same case form when it is Sa (subject of e.g. work) or So (subject of e.g. fall or die)? I.e.: There does not exist a split into stative and active intransitive verbs.; 313 Alignment; Pronoun: Present Progressive; In present progressive: how is the marking of subject and object of pronouns realized?; P:PROG:A=O?; In present progressive: Is the pronoun form for A the same as for O? I.e.: Does the pronoun look the same when it is subject of a transitive clause than when it is object of a transitive clause?; 314 Alignment; Pronoun: Present Progressive; In present progressive: how is the marking of subject and object of pronouns realized?; P:PROG:A=Sa?; In present progressive:Is the pronoun form for A the same as for Sa? I.e.: Does the pronoun look the same when it is subject of a transitive clause as when it is subject of an agentive intransitive verb such as “work” or “dance”?; 315 Alignment; Pronoun: Present Progressive; In present progressive: how is the marking of subject and object of pronouns realized?; P:PROG: O=So?; In present progressive: Is the pronoun form for O the same as for So? I.e.: Does the pronoun look the same when it is object of a transitive clause than when it is subject of an unaccusative verb such as “die” or “fall”?; 316 Alignment; Pronoun: Present Progressive; In present progressive: how is the marking of subject and object of pronouns realized?; P:PROG:Sa=So?; In present progressive: Does a pronoun bear the same case form when it is Sa (subject of e.g. work) or So (subject of e.g. fall or die)? I.e.: There does not exist a split into stative and active intransitive verbs.; 317 Alignment; Verb: Simple Past; In simple past, how is alignment realized on the verb?; V:PST:A=O?; In simple past: Is the verb affix for A the same as for O? I.e.: Does the verb look the same when it refers to the subject of a transitive clause than when it refers to the object of a transitive clause? If there is no O-marking on the verb, but there is an S-marking, the answer would be no, they do not look the same. (e.g., German, Russian) If there is neither an O, nor an A marking, like in Swedish,

410

Appendix 2a: Grammar: Features, complete list (from DiACL)

the answer would be yes, they look the same!; 318 Alignment; Verb: Simple Past; In simple past, how is alignment realized on the verb?; V:PST:A=Sa?; In simple past: Is the verb affix for A the same as for Sa? I.e.: Does the verb look the same when it refers to subject of a transitive clause than when it refers to subject of an agentive intransitive verb like “work” or “dance”?; 319 Alignment; Verb: Simple Past; In simple past, how is alignment realized on the verb?; V:PST:O=So?; In simple past: Is the verb affix for O the same as for So? I.e.: Does the verb look the same when it refers to the object of a transitive clause as when it refers to the subject of an unaccusative verb (such as “fall” or “die”)?; 320 Alignment; Verb: Simple Past; In simple past, how is alignment realized on the verb?; V:PST:Sa=So?; In simple past: Is the verb affix the same for Sa (subject of e.g. work) as or So (subject of e.g. fall or die)? I.e., does the verb agreement affix look the same regardless of whether the verb is “work” or “die” (as in German: “arbeitete-st”, “starb-st”). I.e.: There does not exist a split into unaccusative and agentive intransitive verbs.; 321 Alignment; Verb: Present Progressive; In present progressive, how is alignment realized on the verb?; V:PROG:A=O?; In present progressive: Is the verb affix for A the same as for O? Ie: Does the verb look the same when it refers to the subject of a transitive clause than when it refers to the object of a transitive clause? If there is no O-marking on the verb, but there is an S-marking, the answer would be no, they do not look the same. (e.g. German, Russian) If there is neither an O, nor an A marking like in Swedish, the answer would be yes, they look the same!; 322 Alignment; Verb: Present Progressive; In present progressive, how is alignment realized on the verb?; V:PROG:A=Sa?; In present progressive:Is the verb affix for A the same as for Sa? Ie: Does the verb look the same when it refers to subject of a transitive clause as when it refers to subject of an agentive intransitive verb such as “work”?; 323 Alignment; Verb: Present Progressive; In present progressive, how is alignment realized on the

verb?; V:PROG: O=So?; In present progressive: Is the verb affix the same for O as for So? Ie: Does the verb look the same when it refers to the object of a transitive clause as when it refers to the subject of an unaccusative verb (such as “fall” or “die”)?; 324 Alignment; Verb: Present Progressive; In present progressive, how is alignment realized on the verb?; V:PROG:Sa=So?; In present progressive: Is the verb affix the same for Sa (subject of e.g. “work”) as or So (subject of e.g. “fall” or “die”)? I.e. does the verb agreement affix look the same regardless of whether the verb is “work” or “die” (as in German: arbeite-t, stirb-t). I.e.: There does not exist a split into unaccusative and agentive intransitive verbs.; 325 Alignment; Compare PROG-PAST; What is the marking relation between subject and object in present progressive and simple past?; PROG_So=PAST_So; Does the subject of e.g. die or fall bear the same case in both progressive present and simple past? (the answer for e.g., Megrelian would be no); 326 Alignment; Compare PROG-PAST; What is the marking relation between subject and object in present progressive and simple past?; PROG_A=PAST_O; Does the subject of a transitive verb in the present progressive bear the same case form as the object of a transitive verb in the simple past? (e.g. as in Georgian); 327 Alignment; Compare PROG-PAST; What is the marking relation between subject and object in present progressive and simple past?; PAST_A=PROG_O; Does the subject of a transitive verb in the simple past bear the same case form as the object of a verb in the present progressive? (e.g., Kurdish); 328 Alignment; Reflexive pronoun in transitive clause; What is the alignment of reflexive pronouns?; REFL-refA; In a transitive clause, can O be a reflexive which refers back to A (as in English “herself”, Swedish “sig”)?; 329 Alignment; Reflexive pronoun in transitive clause; What is the alignment of reflexive pronouns?; REFL-refO; In a transitive clause, can A be a reflexive which refers back to O (as appears to be the case in some Caucasian languages)?; 330

Appendix 2b: Grammar: State combinations This appendix gives the occuring state combinations of Features, i.e., the combinations of values fort he Variants of Features of the data of the database DiACL. State combinations, which represent grammatical properties or patterns, are labelled. These labels form the basis for grammar maps. Order of data is as follows: Grammar Feature [a–z] (Abbrevation acronym given in parathesis); Explanation State Combination Map Order [a–z] (Number indicating the fixed order of Variants, of Features, distinguished by /, which are the basis for the state combinations. The number is generated by frequency (1 = most frequent) and corresponds to the number given in maps); State Combination (Combination of 1 and 0 which ist he unique identifier of the state combination); Description (Explanation of grammar property as it is shown in maps legends). Grammar Feature [a–z] (Abbrevation); Explanation State Combination Map Order [a–z]; State Combination; Description).

Agreement with respect to Agent (A) in Present Progressive (VM.PPr.A); PROG:A-AGR-FULL/PROG: A-Gender-AGR/PROG:NO-A-AGR 1; 001; No A Agreement 2; 000; Syncretic A Agreement 3; 100; Full A Agreement 4; 010; Gender A Agreement 5; 110; Full and Gender A Agreement Agreement with respect to Agent in Simple Past (VM.Pst.A); PST:A-AGR-FULL/PST:A-Gender-AGR/ PST:NO-A-AGR 1; 001; No A Agreement 2; 000; Syncretic A Agreement 3; 100; Full A Agreement 4; 010; Gender A Agreement 5; 110; Full and Gender A Agreement Agreement with respect to Dative in Present Progressive (VM.PPr.D); PROG:DAT-AGR-FULL/ PROG:DAT-Gender-AGR/PROG: NO-DAT-AGR 1; 001; No Dative Agreement 2; 000; Syncretic Dative Agreement 3; 100; Full Dative Agreement Agreement with respect to Object in Present Progressive (VM.PPr.O); PROG:NO-O-AGR/PROG: O-AGR-FULL/PROG:O-Gender-AGR 1; 001; No O Agreement 2; 000; Syncretic O Agreement 3; 100; Full O Agreement 4; 010; Gender O Agreement Agreement with respect to Object in Simple Past (VM.Pst.O); PST:NO-O-AGR/PST:O-AGR-FULL/PST: O-Gender-AGR 1; 100; No O Agreement 2; 000; Syncretic O Agreement 3; 010; Full O Agreement 4; 001; Gender O Agreement 5; 011; Full and Gender Agreement Alignment by Nouns in Present Progressive (A.N.PPr); N:PROG: O=So?/N:PROG:A=O?/N:PROG:A=Sa?/ N:PROG:Sa=So? 1; 1111; No marking 2; 1010; Active https://doi.org/10.1515/9783110367416-011

3; 1001; Ergative 4; 0011; Nominative-accusative 5; 0001; Tripartite Alignment by Nouns in Simple Past (A.N.Pst); N:PST: O=So?/N:PST:A=O?/N:PST:A=Sa?/N:PST:Sa=So? 1; 1111; No marking 2; 1010; Active 3; 1001; Ergative 4; 0011; Nominative-accusative 5; 0001; Tripartite Alignment by Pronouns in Present Progressive (A.Pn.PPr); P:PROG: O=So?/P:PROG:A=O?/P:PROG: A=Sa?/P:PROG:Sa=So? 1; 1111; No marking 2; 1010; Active 3; 1001; Ergative 4; 0011; Nominative-accusative Alignment by Pronouns in Simple Past (A.Pn.Pst); P:PST: O=So?/P:PST:A=O?/P:PST:A=Sa?/P:PST:Sa=So? 1; 1111; No marking 2; 1010; Active 3; 1001; Ergative 4; 0011; Nominative-accusative 5; 0001; Tripartite Definiteness marking (NM.Def); ADJ-DEF/DEF-FIRST/ DEF-LAST/DEF.ART/N-DEF 1; 00000; No definiteness marking 2; 00001; Definiteness on the noun 3; 00010; Definite article 4; 00011; Definite article and definiteness on the noun 5; 00100; Definiteness on the last element of the NP 6; 00101; Definiteness marking on the last element of the NP and on the noun 7; 01000; Definiteness on the first member of the NP 8; 01001; Definiteness on the first element of the NP and definiteness on the noun 9; 01010; Definiteness on the first element of NP and definite article 10; 10000; Definiteness on the adjective 11; 10001; Definiteness marking on the adjective and on the noun

412

Appendix 2b: Grammar: State combinations

12; 10010; Definiteness marking on the adjective and definite article 13; 10101; Definiteness on the last member of the NP, on the adjective, and on the noun Future tense marking (T.Fut); FUT.AUX/FUT.Participle/ FUT.Particle/FUT.Synth/PERF.FUT 1; 00000; No future 2; 10000; Future by auxiliary 3; 01000; Future by participle 4; 00100; Future by particle 5; 00001; Future by perfect 6; 00010; Synthetic future 7; 11000; Future by auxiliary and by participle 8; 10100; Future by auxiliary and by particle 9; 10001; Future by auxiliary and by perfect 10; 10010; Future by auxiliary and synthetic future 11; 01010; Future by participle and synthetic future 12; 00110; Future by particle and synthetic future 13; 11010; Future by auxiliary, by participle, and synthetic future 14; 10110; Future by auxiliary, by particle, and synthetic future 15; 10011; Future by participle, synthetic future, and future by perfect 16; 01111; Future by participle, by particle, synthetic future, and by perfect Gender and Noun class marking (NM.Gen); < 5 GENDER/ ANIM/M/F/NEUTR 1; 0000; No gender marking 2; 0001; Distinction of a default and a neuter gender 3; 0010; Masculine – feminine distinction 4; 0011; Masculine – feminine – neuter distinction 5; 0100; Special noun class for non-human animates 6; 0110; Distinction of masculine, feminine, and noun class of non-human animates 7; 0111; Distinction of non-human animate, masculine, feminine and neuter 8; 1110; More than five genders, including non-human animate, masculine, feminine, and neuter Nominal case system (NM.Case.N); AGGL_REPLACE/ GEN_DAT_REPLACED/O-case/OBL-Cases 1; 0000; No agglutinative tendency, no genitive and/or dative, no A/O distinction, no local cases 2; 0010; No agglutinative tendency, no genitive and/or dative, A/O distinction, no local cases 3; 0011; No agglutinative tendency, no genitive and/or dative, A/O distinction, local cases 4; 0100; No agglutinative tendency, genitive and/or dative, no A/O distinction, no local cases 5; 0110; No agglutinative tendency, genitive and/or dative, A/O distinction, no local cases 6; 0111; No agglutinative tendency, genitive and/or dative, A/O distinction, local cases 7; 1001; Agglutinative tendency, no genitive and/or dative, no A/O distinction, local cases 8; 1011; Agglutinative tendency, no genitive and/or dative, A/O distinction, local cases 9; 1100; Agglutinative tendency, genitive and/or dative, no A/O distinction, no local cases

10; 1101; Agglutinative tendency, genitive and/or dative, no A/O distinction, local cases 11; 1110; Agglutinative tendency, genitive and/or dative, A/O distinction, no local cases 12; 1111; Agglutinative tendency, genitive and/or dative, A/O distinction, local cases Position of Question word (WO.WH); WH-V/WH-initial 1; 00; Variation allowed 2; 01; WH-initial (no inversion) 3; 10; WH – Verb (initial or not) 4; 11; WH-initial and WH – Verb Pronominal case system (NM.Case.Pn); AGGL_REPLACE/ A_DIFF_O/DAT_DIFF_O/LOC_CASES 1; 0000; No agglutinative tendency, no A/O distinction, no DAT/O distinction, no local cases 2; 0001; No agglutinative tendency, no A/O distinction, no DAT/O distinction, local cases 3; 0100; No agglutinative tendency, A/O distinction, no DAT/O distinction, no local cases 4; 0101; No agglutinative tendency, A/O distinction, no DAT/O distinction, local cases 5; 0110; No agglutinative tendency, A/O distinction, DAT/O distinction, no local cases 6; 0111; No agglutinative tendency, A/O distinction, DAT/O distinction, local cases 7; 1001; Agglutinative tendency, no A/O distinction, no DAT/O distinction, local cases 8; 1011; Agglutinative tendency, no A/O distinction, DAT/O distinction, local cases 9; 1100; Agglutinative tendency, A/O distinction, no DAT/O distinction, no local cases 10; 1101; Agglutinative tendency, A/O distinction, no DAT/O distinction, local cases 11; 1110; Agglutinative tendency, A/O distinction, DAT/ O distinction, no local cases 12; 1111; Agglutinative tendency, A/O distinction, DAT/ O distinction, local cases Realization of case marking in a Noun Phrase (NM.Case); CASE-ADJ/CASE-ART/CASE-FIRST/ CASE-LAST/CASE-N 1; 00000; No case marking 2; 00001; Case only on the noun 3; 00010; Case obligatory on the last member of the NP 4; 00011; Case obligatory on the last member of the NP and case and on the noun 5; 01001; Case marking on the article and case on the noun 6; 10001; Case marking on the adjective and on the noun 7; 10011; Case on the adjective, the last member of the NP, and on the noun 8; 11000; Case on the adjective and on the article 9; 11001; Case marking in the adjective, on the article, and on the noun Word order Adposition − Noun (WO.Adp); Post/Prep 1; 01; Prepositions 2; 10; Postpositions 3; 11; Both post/prepositions

Appendix 2b: Grammar: State combinations

Word order Clitic Pronoun – Finite Verb (Predicate) (WO.Cl.Fin); 2nd position/OV/VO 1; 000; Category irrelevant 2; 001; Verb – Object 3; 010; Object – Verb 4; 011; Verb – Object and Object – Verb 5; 100; 2nd position Word order Clitic Pronoun – Infinitive Verb (WO.Cl.Inf); 2nd position/OV/VO 1; 000; Category irrelevant 2; 001; Verb – Object 3; 010; Object – Verb 4; 011; Object – Verb and Verb − Object 5; 100; 2nd position Word order Clitic Pronoun – Participle Verb (WO.Cl.Ptc); 2nd position/OV/VO 1; 000; Category irrelevant 2; 001; Verb − Object 3; 010; Object – Verb 4; 011; Object – Verb and Verb – Object 5; 100; 2nd position Word order in Main Clauses (WO.MC); SOV/SVO/V2/ VSO 1; 0100; Subject – Verb – Object 2; 1000; Subject – Object – Verb 3; 1100; Subject – Object – Verb and Subject – Verb – Object 4; 0001; Verb – Subject – Object 5; 0010; Verb 2nd Word order Noun − Adjective (WO.Adj); AN/NA 1; 10; Adjective – Noun

413

2; 01; Noun – Adjective 3; 11; Adjective – Noun and Noun – Adjective Word order Noun – Possessor (Genitive) (WO.Poss); N-Poss/Poss-N 1; 01; Possessor – Noun 2; 10; Noun – Possessor 3; 11; Possessor – Noun and Noun – Possessor Word order Noun – Relative clause (WO.RC); NRel/RelN 1; 01; Relative – Noun 2; 10; Noun – Relative 3; 11; Relative − Noun and Noun – Relative 4; 00; Category irrelevant Word order Object – Infinitive (WO.Inf); OV/VO 1; 00; Category irrelevant 2; 01; Verb – Object 3; 10; Object – Verb 4; 11; Object – Verb or Verb – Object Word order Object − Participle (WO.Ptc); OV/VO 1; 01; Participle – Object 2; 10; Object – Participle 3; 11; Participle – Object and Object – Participle 4; 00; Category irrelevant Word order Subordinate Clause (WO.Sub); SOV/SVO/ V2/VSO 1; 0100; Subject – Verb – Object 2; 1000; Subject – Object – Verb 3; 1100; Subject – Object – Verb and Subject – Verb – Object 4; 0001; Verb – Subject – Object 5; 0010; Verb 2nd

Appendix 2c: Grammar: State combinations in languages This appendix gives the state combinations of languages for all Features in the data. Features are listed by their acronyms of appendix 2b, and state combinations follow the fixed Variant order described in appendix 2b. (Language Name [a–z]; Grammar States).

Albanian (Tosk); A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 01001; NM.Def: 01000; NM.Gen: 0010; T.Fut: 00100; VM.PPr.A: 000; VM.PPr.D: 100; VM.PPr.O: 010; VM.Pst.A: 100; VM.Pst.O: 010; WO.Adp: 01; WO.Cl.Fin: 010; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 00; WO.MC: 0100; WO.Poss: 10; WO.Adj: 01; WO.RC: 10; WO.Ptc: –; WO.Sub: 0100; WO.WH: 01; NM.Case.N: 0111; NM.Case.Pn: 0111 Angloromani; A.N.PPr: 1111; A.N.Pst: 1111; A.Pn.PPr: 1111; A.Pn.Pst: 1111; NM.Case: 00000; NM.Def: 01010; NM.Gen: 0000; T.Fut: 10000; VM.PPr.A: 000; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 001; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 01; WO.MC: 0100; WO.Poss: 01; WO.Adj: 10; WO.RC: 10; WO.Ptc: 01; WO.Sub: 0100; WO.WH: –; NM.Case.N: 0100; NM.Case.Pn: 0000 Ashkun; A.N.PPr: 0011; A.N.Pst: 1001; A.Pn.PPr: 0011; A.Pn.Pst: 1001; NM.Case: 00011; NM.Def: 00000; NM.Gen: 0010; T.Fut: 00010; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 001; VM.Pst.O: 010; WO.Adp: 10; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 1000; WO.Poss: 01; WO.Adj: 10; WO.RC: –; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 10; NM.Case.N: 0111; NM.Case.Pn: 1110 Assamese; A.N.PPr: 0001; A.N.Pst: 0001; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: –; NM.Def: 00001; NM.Gen: 1110; T.Fut: 00010; VM.PPr.A: 000; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 000; VM.Pst.O: 100; WO.Adp: 10; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 1000; WO.Poss: 01; WO.Adj: 10; WO.RC: 01; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 00; NM.Case.N: 1111; NM.Case.Pn: 1111 Avestan; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 10001; NM.Def: 00000; NM.Gen: 0011; T.Fut: 00010; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 100; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 100; WO.Cl.Inf: 100; WO.Cl.Ptc: 100; WO.Inf: 10; WO.MC: 1000; WO.Poss: 01; WO.Adj: 10; WO.RC: 10; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 01; NM.Case.N: 0111; NM.Case.Pn: 0111 Baluchi; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 00011; NM.Def: 00101; NM.Gen: 0000; T.Fut: 10000; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 100; https://doi.org/10.1515/9783110367416-012

VM.Pst.O: 100; WO.Adp: 11; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 1000; WO.Poss: 01; WO.Adj: 10; WO.RC: 01; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 00; NM.Case.N: 1110; NM.Case.Pn: 0110 Basque (East); A.N.PPr: 1111; A.N.Pst: 1001; A.Pn.PPr: 1111; A.Pn.Pst: 1001; NM.Case: –; NM.Def: 00100; NM.Gen: 0000; T.Fut: 01000; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 000; VM.Pst.A: 100; VM.Pst.O: 010; WO.Adp: 10; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 1000; WO.Poss: 01; WO.Adj: 01; WO.RC: 01; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 10; NM.Case.N: 1111; NM.Case.Pn: 1111 Basque (West); A.N.PPr: 1111; A.N.Pst: 1010; A.Pn.PPr: 1111; A.Pn.Pst: 1010; NM.Case: 00010; NM.Def: 00100; NM.Gen: 0000; T.Fut: 01000; VM.PPr.A: 100; VM.PPr.D: 100; VM.PPr.O: 000; VM.Pst.A: 100; VM.Pst.O: 010; WO.Adp: 10; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 1000; WO.Poss: 01; WO.Adj: 01; WO.RC: 01; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 10; NM.Case.N: 1111; NM.Case.Pn: 1111 Batsbi; A.N.PPr: 0011; A.N.Pst: 1010; A.Pn.PPr: 1111; A.Pn.Pst: 1111; NM.Case: 00011; NM.Def: 00000; NM.Gen: 0110; T.Fut: 00001; VM.PPr.A: 001; VM.PPr.D: 001; VM.PPr.O: 010; VM.Pst.A: 100; VM.Pst.O: 011; WO.Adp: 10; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 1000; WO.Poss: 01; WO.Adj: 10; WO.RC: 11; WO.Ptc: 01; WO.Sub: 1000; WO.WH: 10; NM.Case.N: 1111; NM.Case.Pn: 0000 Bengali; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 00011; NM.Def: 00101; NM.Gen: 0100; T.Fut: 00010; VM.PPr.A: 000; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 000; VM.Pst.O: 100; WO.Adp: 10; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 1000; WO.Poss: 01; WO.Adj: 10; WO.RC: 01; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 00; NM.Case.N: 1111; NM.Case.Pn: 1100 Breton; A.N.PPr: 1111; A.N.Pst: 1111; A.Pn.PPr: 1111; A.Pn.Pst: 1111; NM.Case: 00000; NM.Def: 00011; NM.Gen: 0010; T.Fut: 00010; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: –; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 00; WO.MC: 0010; WO.Poss: 10; WO.Adj: 01; WO.RC: 10; WO.Ptc: 01; WO.Sub: 0001; WO.WH: –; NM.Case.N: 0000; NM.Case.Pn: 0000

Appendix 2c: Grammar: State combinations in languages

Bulgarian; A.N.PPr: 1111; A.N.Pst: 1111; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 00000; NM.Def: 01000; NM.Gen: 0011; T.Fut: 10100; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 000; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 001; WO.Cl.Inf: 000; WO.Cl.Ptc: 001; WO.Inf: 00; WO.MC: 0100; WO.Poss: 10; WO.Adj: 10; WO.RC: 10; WO.Ptc: 01; WO.Sub: 0100; WO.WH: 00; NM.Case.N: 0000; NM.Case.Pn: 0110 Catalan; A.N.PPr: 1111; A.N.Pst: 1111; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 00000; NM.Def: 01010; NM.Gen: 0010; T.Fut: 00010; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 000; VM.Pst.O: 000; WO.Adp: 01; WO.Cl.Fin: 010; WO.Cl.Inf: 001; WO.Cl.Ptc: 001; WO.Inf: 01; WO.MC: 0100; WO.Poss: 10; WO.Adj: 01; WO.RC: 10; WO.Ptc: 01; WO.Sub: 0100; WO.WH: 11; NM.Case.N: 0000; NM.Case.Pn: 0100 Classical Greek; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 11001; NM.Def: 01010; NM.Gen: 0011; T.Fut: 01000; VM.PPr.A: 100; VM.PPr.D: 000; VM.PPr.O: 000; VM.Pst.A: 100; VM.Pst.O: 000; WO.Adp: 01; WO.Cl.Fin: 011; WO.Cl.Inf: 011; WO.Cl.Ptc: 011; WO.Inf: 11; WO.MC: 1000; WO.Poss: 11; WO.Adj: 11; WO.RC: 10; WO.Ptc: 11; WO.Sub: 1000; WO.WH: 01; NM.Case.N: 0110; NM.Case.Pn: 0100 Cornish; A.N.PPr: 1111; A.N.Pst: 1111; A.Pn.PPr: 1111; A.Pn.Pst: 1111; NM.Case: 00000; NM.Def: 00011; NM.Gen: 0010; T.Fut: 10000; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 100; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 00; WO.MC: 0100; WO.Poss: –; WO.Adj: 01; WO.RC: 10; WO.Ptc: –; WO.Sub: 1000; WO.WH: –; NM.Case.N: 0000; NM.Case.Pn: 0000 Croatian; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 10001; NM.Def: 10000; NM.Gen: 0011; T.Fut: 10000; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 110; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 100; WO.Cl.Inf: 100; WO.Cl.Ptc: 100; WO.Inf: 01; WO.MC: 0100; WO.Poss: 10; WO.Adj: 10; WO.RC: 10; WO.Ptc: 01; WO.Sub: 0100; WO.WH: 11; NM.Case.N: 0111; NM.Case.Pn: 0111 Czech; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 10001; NM.Def: 00000; NM.Gen: 0011; T.Fut: 10001; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 110; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 011; WO.Cl.Inf: 011; WO.Cl.Ptc: 011; WO.Inf: 01; WO.MC: 0100; WO.Poss: 01; WO.Adj: 10; WO.RC: 10; WO.Ptc: 01; WO.Sub: 0100; WO.WH: 01; NM.Case.N: 0111; NM.Case.Pn: 0111 Danish; A.N.PPr: 1111; A.N.Pst: 1111; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 00000; NM.Def: 10001; NM.Gen: 0001; T.Fut: 10000; VM.PPr.A: 001; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 001;

415

VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 01; WO.MC: 0010; WO.Poss: 01; WO.Adj: 10; WO.RC: 10; WO.Ptc: 01; WO.Sub: 0100; WO.WH: 11; NM.Case.N: 0000; NM.Case.Pn: 0100 Dutch; A.N.PPr: 1111; A.N.Pst: 1111; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 00000; NM.Def: 01010; NM.Gen: 0001; T.Fut: 10000; VM.PPr.A: 000; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 001; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 0010; WO.Poss: 10; WO.Adj: 10; WO.RC: 10; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 11; NM.Case.N: 0000; NM.Case.Pn: 0100 Elfdalian; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 11001; NM.Def: 10001; NM.Gen: 0011; T.Fut: 10000; VM.PPr.A: 000; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 000; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 01; WO.MC: 0010; WO.Poss: 11; WO.Adj: 10; WO.RC: 10; WO.Ptc: 01; WO.Sub: 0010; WO.WH: 11; NM.Case.N: 1110; NM.Case.Pn: 0100 English; A.N.PPr: 1111; A.N.Pst: 1111; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 00000; NM.Def: 01010; NM.Gen: 0000; T.Fut: 10000; VM.PPr.A: 000; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 001; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 01; WO.MC: 0100; WO.Poss: 01; WO.Adj: 10; WO.RC: 10; WO.Ptc: 01; WO.Sub: 0100; WO.WH: 11; NM.Case.N: 0000; NM.Case.Pn: 0100 Estonian; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 10001; NM.Def: 00000; NM.Gen: 0000; T.Fut: 10000; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 000; VM.Pst.O: 100; WO.Adp: 10; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 0100; WO.Poss: 01; WO.Adj: 10; WO.RC: 10; WO.Ptc: 10; WO.Sub: 0100; WO.WH: 01; NM.Case.N: 1111; NM.Case.Pn: 0111 Faroese; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 11001; NM.Def: 10001; NM.Gen: 0011; T.Fut: –; VM.PPr.A: 000; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 001; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 01; WO.MC: 0010; WO.Poss: 10; WO.Adj: 10; WO.RC: 10; WO.Ptc: 01; WO.Sub: 0010; WO.WH: 11; NM.Case.N: 1110; NM.Case.Pn: 0110 Finnish; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 10001; NM.Def: 00000; NM.Gen: 0000; T.Fut: 10000; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 100; VM.Pst.O: 100; WO.Adp: 10; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 01; WO.MC: 0100; WO.Poss: 01; WO.Adj: 10; WO.RC: 10; WO.Ptc: 01; WO.Sub: 0100; WO.WH: 01; NM.Case.N: 1111; NM.Case.Pn: 0111

416

Appendix 2c: Grammar: State combinations in languages

French; A.N.PPr: 1111; A.N.Pst: 1111; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 00000; NM.Def: 01010; NM.Gen: 0010; T.Fut: 10010; VM.PPr.A: 000; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 000; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 010; WO.Cl.Inf: 010; WO.Cl.Ptc: 010; WO.Inf: 01; WO.MC: 0100; WO.Poss: 10; WO.Adj: 01; WO.RC: 10; WO.Ptc: 01; WO.Sub: 0100; WO.WH: 01; NM.Case.N: 0000; NM.Case.Pn: 0100 Frisian; A.N.PPr: 1111; A.N.Pst: 1111; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 00000; NM.Def: 10010; NM.Gen: 0001; T.Fut: 10000; VM.PPr.A: 000; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 000; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 001; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 0010; WO.Poss: 10; WO.Adj: 10; WO.RC: 10; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 11; NM.Case.N: 0000; NM.Case.Pn: 0100 Friulian; A.N.PPr: 1111; A.N.Pst: 1111; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 00000; NM.Def: –; NM.Gen: 0010; T.Fut: –; VM.PPr.A: 000; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 000; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 010; WO.Cl.Inf: 001; WO.Cl.Ptc: 001; WO.Inf: –; WO.MC: 0100; WO.Poss: 10; WO.Adj: 01; WO.RC: 10; WO.Ptc: –; WO.Sub: 0100; WO.WH: –; NM.Case.N: 0000; NM.Case.Pn: 0110 Georgian; A.N.PPr: 0011; A.N.Pst: 1010; A.Pn.PPr: 1111; A.Pn.Pst: 1111; NM.Case: 00001; NM.Def: 00000; NM.Gen: 0000; T.Fut: 00001; VM.PPr.A: 100; VM.PPr.D: 100; VM.PPr.O: 010; VM.Pst.A: 100; VM.Pst.O: 010; WO.Adp: 10; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 00; WO.MC: 1000; WO.Poss: 01; WO.Adj: 10; WO.RC: 10; WO.Ptc: 00; WO.Sub: 1000; WO.WH: 10; NM.Case.N: 1111; NM.Case.Pn: 0001 German; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 11001; NM.Def: 10010; NM.Gen: 0011; T.Fut: 10000; VM.PPr.A: 000; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 000; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 0010; WO.Poss: 10; WO.Adj: 10; WO.RC: 10; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 11; NM.Case.N: 0110; NM.Case.Pn: 0110 Gilaki; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 00010; NM.Def: 00011; NM.Gen: 0000; T.Fut: 10000; VM.PPr.A: 000; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 000; VM.Pst.O: 100; WO.Adp: 11; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 1000; WO.Poss: 01; WO.Adj: 10; WO.RC: 10; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 00; NM.Case.N: 1111; NM.Case.Pn: – Gothic; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 11001; NM.Def: 10010; NM.Gen: 0011; T.Fut: 10000; VM.PPr.A: 000; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 000; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 000;

WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 1000; WO.Poss: 10; WO.Adj: 01; WO.RC: 10; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 01; NM.Case.N: 0110; NM.Case.Pn: 0110 Gujarati; A.N.PPr: 0011; A.N.Pst: 1001; A.Pn.PPr: 0011; A.Pn.Pst: 1001; NM.Case: 10001; NM.Def: 00000; NM.Gen: 0011; T.Fut: 00010; VM.PPr.A: 000; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 001; VM.Pst.O: 001; WO.Adp: 10; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 1000; WO.Poss: 01; WO.Adj: 10; WO.RC: 01; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 10; NM.Case.N: 1011; NM.Case.Pn: 0101 Hindi; A.N.PPr: 0011; A.N.Pst: 1001; A.Pn.PPr: 0011; A.Pn.Pst: 1001; NM.Case: 10001; NM.Def: 00000; NM.Gen: 0010; T.Fut: 00010; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 001; VM.Pst.O: 001; WO.Adp: 10; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 1000; WO.Poss: 01; WO.Adj: 10; WO.RC: 10; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 10; NM.Case.N: –; NM.Case.Pn: 0100 Hittite; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 10001; NM.Def: 00000; NM.Gen: 0001; T.Fut: –; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 000; VM.Pst.O: 100; WO.Adp: 10; WO.Cl.Fin: 100; WO.Cl.Inf: 100; WO.Cl.Ptc: 100; WO.Inf: 10; WO.MC: 1000; WO.Poss: 01; WO.Adj: 10; WO.RC: 01; WO.Ptc: 10; WO.Sub: 1000; WO.WH: –; NM.Case.N: 0111; NM.Case.Pn: 0101 Hungarian; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 00010; NM.Def: 00010; NM.Gen: 0000; T.Fut: 10000; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 100; VM.Pst.O: 000; WO.Adp: 10; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 11; WO.MC: 0100; WO.Poss: 01; WO.Adj: 10; WO.RC: 10; WO.Ptc: 11; WO.Sub: 0100; WO.WH: 10; NM.Case.N: 1111; NM.Case.Pn: 1111 Icelandic; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 11001; NM.Def: 10001; NM.Gen: 0011; T.Fut: 10000; VM.PPr.A: 000; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 000; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 01; WO.MC: 0010; WO.Poss: 10; WO.Adj: 10; WO.RC: 10; WO.Ptc: 01; WO.Sub: 0010; WO.WH: 11; NM.Case.N: 0110; NM.Case.Pn: 0110 Irish; A.N.PPr: 0011; A.N.Pst: 1111; A.Pn.PPr: 0011; A.Pn.Pst: 1111; NM.Case: 11001; NM.Def: 00011; NM.Gen: 0010; T.Fut: 00010; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 100; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 0001; WO.Poss: 10; WO.Adj: 01; WO.RC: 10; WO.Ptc: 01; WO.Sub: 0001; WO.WH: 11; NM.Case.N: 0100; NM.Case.Pn: 0000

Appendix 2c: Grammar: State combinations in languages

Italian; A.N.PPr: 1111; A.N.Pst: 1111; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 00000; NM.Def: 01010; NM.Gen: 0010; T.Fut: 00010; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 100; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 010; WO.Cl.Inf: 001; WO.Cl.Ptc: 001; WO.Inf: 01; WO.MC: 0100; WO.Poss: 10; WO.Adj: 01; WO.RC: 10; WO.Ptc: 01; WO.Sub: 0100; WO.WH: 01; NM.Case.N: 0000; NM.Case.Pn: 0100 Kabardian; A.N.PPr: 1001; A.N.Pst: 1001; A.Pn.PPr: 1111; A.Pn.Pst: 1111; NM.Case: 00010; NM.Def: 00000; NM.Gen: 0000; T.Fut: 00010; VM.PPr.A: 100; VM.PPr.D: 100; VM.PPr.O: 010; VM.Pst.A: 100; VM.Pst.O: 010; WO.Adp: 10; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: –; WO.MC: 1000; WO.Poss: 01; WO.Adj: 01; WO.RC: 00; WO.Ptc: –; WO.Sub: 1000; WO.WH: 10; NM.Case.N: 1011; NM.Case.Pn: 1001 Karachay-Balkar; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 00011; NM.Def: 00001; NM.Gen: 0000; T.Fut: 00010; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 100; VM.Pst.O: 100; WO.Adp: 10; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: –; WO.MC: 1000; WO.Poss: 01; WO.Adj: 10; WO.RC: 01; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 10; NM.Case.N: 1111; NM.Case.Pn: 1111 Kashmiri; A.N.PPr: 1111; A.N.Pst: 1001; A.Pn.PPr: 1111; A.Pn.Pst: 1001; NM.Case: 00011; NM.Def: 00000; NM.Gen: 0010; T.Fut: 00010; VM.PPr.A: 010; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 001; VM.Pst.O: 001; WO.Adp: 10; WO.Cl.Fin: 001; WO.Cl.Inf: 010; WO.Cl.Ptc: 010; WO.Inf: 10; WO.MC: 0010; WO.Poss: 01; WO.Adj: 10; WO.RC: 10; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 10; NM.Case.N: 0111; NM.Case.Pn: 0111 Kati; A.N.PPr: 0011; A.N.Pst: 1001; A.Pn.PPr: 0011; A.Pn.Pst: 1001; NM.Case: 00011; NM.Def: 00000; NM.Gen: 0010; T.Fut: 01010; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 001; VM.Pst.O: 011; WO.Adp: 10; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 1000; WO.Poss: 01; WO.Adj: 10; WO.RC: –; WO.Ptc: 10; WO.Sub: –; WO.WH: 00; NM.Case.N: 1110; NM.Case.Pn: 1100 Kazakh; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 00011; NM.Def: 00000; NM.Gen: 0000; T.Fut: 00000; VM.PPr.A: 000; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 000; VM.Pst.O: 100; WO.Adp: 10; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 1000; WO.Poss: 01; WO.Adj: 10; WO.RC: 01; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 10; NM.Case.N: 1111; NM.Case.Pn: 1111 Khowar; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 01001; NM.Def: 01010; NM.Gen: 0100; T.Fut: 00010; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 000;

417

VM.Pst.O: 100; WO.Adp: 10; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 1000; WO.Poss: 01; WO.Adj: 10; WO.RC: 10; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 10; NM.Case.N: 1011; NM.Case.Pn: 0100 Khwarshi; A.N.PPr: 1001; A.N.Pst: 1001; A.Pn.PPr: 1001; A.Pn.Pst: 1001; NM.Case: 00001; NM.Def: 00000; NM.Gen: 0111; T.Fut: 11010; VM.PPr.A: 001; VM.PPr.D: 001; VM.PPr.O: 001; VM.Pst.A: 000; VM.Pst.O: 001; WO.Adp: 10; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 1000; WO.Poss: 01; WO.Adj: 10; WO.RC: 00; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 00; NM.Case.N: 1111; NM.Case.Pn: – Konkani; A.N.PPr: 0011; A.N.Pst: 1001; A.Pn.PPr: 0011; A.Pn.Pst: 1001; NM.Case: 00011; NM.Def: 00000; NM.Gen: 0011; T.Fut: 01010; VM.PPr.A: 000; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 001; VM.Pst.O: 001; WO.Adp: 10; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 1000; WO.Poss: 01; WO.Adj: 10; WO.RC: –; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 10; NM.Case.N: 1111; NM.Case.Pn: 1101 Kryz; A.N.PPr: 1001; A.N.Pst: 1001; A.Pn.PPr: 1111; A.Pn.Pst: 1111; NM.Case: 00011; NM.Def: 00000; NM.Gen: 0111; T.Fut: 00010; VM.PPr.A: 001; VM.PPr.D: 001; VM.PPr.O: 001; VM.Pst.A: 001; VM.Pst.O: 001; WO.Adp: 10; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 1000; WO.Poss: 01; WO.Adj: 10; WO.RC: 00; WO.Ptc: 00; WO.Sub: 1000; WO.WH: 10; NM.Case.N: 1111; NM.Case.Pn: 1011 Kurdish (Kurmanji); A.N.PPr: 0011; A.N.Pst: 1001; A.Pn.PPr: 0011; A.Pn.Pst: 1001; NM.Case: 00001; NM.Def: 00000; NM.Gen: 0010; T.Fut: 00100; VM.PPr.A: 000; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 001; VM.Pst.O: 000; WO.Adp: 01; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 1000; WO.Poss: 10; WO.Adj: 01; WO.RC: 10; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 10; NM.Case.N: 0010; NM.Case.Pn: 0100 Kurdish (Sorani); A.N.PPr: 1111; A.N.Pst: 1001; A.Pn.PPr: 0011; A.Pn.Pst: 1001; NM.Case: 00000; NM.Def: 10101; NM.Gen: 0000; T.Fut: 00000; VM.PPr.A: 000; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 000; VM.Pst.O: 000; WO.Adp: 01; WO.Cl.Fin: 010; WO.Cl.Inf: 010; WO.Cl.Ptc: 010; WO.Inf: 10; WO.MC: 1000; WO.Poss: 10; WO.Adj: 01; WO.RC: 10; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 00; NM.Case.N: 0000; NM.Case.Pn: 0000 Ladin; A.N.PPr: 1111; A.N.Pst: 1111; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 00000; NM.Def: –; NM.Gen: 0010; T.Fut: –; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 000; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 010; WO.Cl.Inf: 010; WO.Cl.Ptc: 010; WO.Inf: 01;

418

Appendix 2c: Grammar: State combinations in languages

WO.MC: 0100; WO.Poss: 10; WO.Adj: 01; WO.RC: 10; WO.Ptc: –; WO.Sub: 0100; WO.WH: –; NM.Case.N: 0000; NM.Case.Pn: 0110 Latin; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 11001; NM.Def: 00000; NM.Gen: 0011; T.Fut: 00010; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 100; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 1000; WO.Poss: 10; WO.Adj: 01; WO.RC: 10; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 01; NM.Case.N: 0111; NM.Case.Pn: 0111 Latvian; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 10001; NM.Def: 10000; NM.Gen: 0010; T.Fut: 00010; VM.PPr.A: 000; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 000; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 01; WO.MC: 0100; WO.Poss: 01; WO.Adj: 10; WO.RC: 10; WO.Ptc: 01; WO.Sub: 0100; WO.WH: –; NM.Case.N: 0111; NM.Case.Pn: 0111 Laz; A.N.PPr: 1010; A.N.Pst: 1010; A.Pn.PPr: 1111; A.Pn.Pst: 1111; NM.Case: 00011; NM.Def: 00000; NM.Gen: 0000; T.Fut: 10010; VM.PPr.A: 100; VM.PPr.D: 100; VM.PPr.O: 010; VM.Pst.A: 100; VM.Pst.O: 010; WO.Adp: 10; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 00; WO.MC: 1000; WO.Poss: 01; WO.Adj: 10; WO.RC: 01; WO.Ptc: 00; WO.Sub: 1000; WO.WH: 10; NM.Case.N: 1111; NM.Case.Pn: 0001 Lezgian; A.N.PPr: 1010; A.N.Pst: 1010; A.Pn.PPr: 1010; A.Pn.Pst: 1010; NM.Case: 00011; NM.Def: 00000; NM.Gen: 0000; T.Fut: 01010; VM.PPr.A: 001; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 001; VM.Pst.O: 100; WO.Adp: 10; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 1000; WO.Poss: 01; WO.Adj: 10; WO.RC: 00; WO.Ptc: 00; WO.Sub: 1000; WO.WH: 10; NM.Case.N: 1111; NM.Case.Pn: 0111 Lithuanian; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 10001; NM.Def: 10000; NM.Gen: 0010; T.Fut: 00010; VM.PPr.A: 000; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 000; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 11; WO.MC: 0100; WO.Poss: 01; WO.Adj: 10; WO.RC: 10; WO.Ptc: 11; WO.Sub: 0100; WO.WH: 01; NM.Case.N: 0111; NM.Case.Pn: 0111 Low_German; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 11000; NM.Def: 10010; NM.Gen: 0011; T.Fut: 10000; VM.PPr.A: 000; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 000; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 0010; WO.Poss: 11; WO.Adj: 10; WO.RC: 10; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 11; NM.Case.N: 0010; NM.Case.Pn: 0100 Luwian; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 10001; NM.Def: 00000;

NM.Gen: 0001; T.Fut: 00000; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 000; VM.Pst.O: 100; WO.Adp: 10; WO.Cl.Fin: 100; WO.Cl.Inf: 100; WO.Cl.Ptc: 100; WO.Inf: 10; WO.MC: 1000; WO.Poss: 01; WO.Adj: 10; WO.RC: 01; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 01; NM.Case.N: 1111; NM.Case.Pn: 0101 Maithili; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 00011; NM.Def: 00000; NM.Gen: 0100; T.Fut: 10010; VM.PPr.A: 000; VM.PPr.D: 000; VM.PPr.O: 000; VM.Pst.A: 000; VM.Pst.O: 000; WO.Adp: 10; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 1000; WO.Poss: 01; WO.Adj: 10; WO.RC: 10; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 10; NM.Case.N: 1111; NM.Case.Pn: – Maldivian; A.N.PPr: 1111; A.N.Pst: 1111; A.Pn.PPr: 1111; A.Pn.Pst: 1111; NM.Case: 00011; NM.Def: 00101; NM.Gen: 0000; T.Fut: 00010; VM.PPr.A: 001; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 000; VM.Pst.O: 100; WO.Adp: 10; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 1000; WO.Poss: 01; WO.Adj: 10; WO.RC: 01; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 00; NM.Case.N: 1101; NM.Case.Pn: – Manx; A.N.PPr: 1111; A.N.Pst: 1111; A.Pn.PPr: 1111; A.Pn.Pst: 1111; NM.Case: 00001; NM.Def: 00011; NM.Gen: 0010; T.Fut: 00010; VM.PPr.A: 000; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 001; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 01; WO.MC: 0001; WO.Poss: 10; WO.Adj: 01; WO.RC: 10; WO.Ptc: 01; WO.Sub: 0001; WO.WH: 11; NM.Case.N: 0100; NM.Case.Pn: 0000 Marathi; A.N.PPr: 0011; A.N.Pst: 1001; A.Pn.PPr: 0011; A.Pn.Pst: 1001; NM.Case: 00011; NM.Def: 00000; NM.Gen: 0011; T.Fut: 00010; VM.PPr.A: 010; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 000; VM.Pst.O: 001; WO.Adp: 10; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 1000; WO.Poss: 01; WO.Adj: 10; WO.RC: 01; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 00; NM.Case.N: 1111; NM.Case.Pn: 1111 Megrelian; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 1111; A.Pn.Pst: 1111; NM.Case: 00001; NM.Def: 00000; NM.Gen: 0000; T.Fut: 00001; VM.PPr.A: 100; VM.PPr.D: 100; VM.PPr.O: 010; VM.Pst.A: 100; VM.Pst.O: 010; WO.Adp: 10; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 00; WO.MC: 1000; WO.Poss: 01; WO.Adj: 10; WO.RC: 10; WO.Ptc: 00; WO.Sub: 1000; WO.WH: 10; NM.Case.N: 1111; NM.Case.Pn: 0001 Middle Breton; A.N.PPr: 1111; A.N.Pst: 1111; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 00000; NM.Def: 00011; NM.Gen: 0010; T.Fut: 00010; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: –; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 010; WO.Cl.Inf: 000; WO.Cl.Ptc: 010;

Appendix 2c: Grammar: State combinations in languages

WO.Inf: 00; WO.MC: 0100; WO.Poss: 10; WO.Adj: 01; WO.RC: 10; WO.Ptc: –; WO.Sub: –; WO.WH: –; NM.Case.N: 0000; NM.Case.Pn: 0000 Middle Dutch; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 11001; NM.Def: 10010; NM.Gen: 0011; T.Fut: 10000; VM.PPr.A: 000; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 000; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 001; WO.Cl.Inf: 010; WO.Cl.Ptc: 010; WO.Inf: 10; WO.MC: 0010; WO.Poss: 11; WO.Adj: 11; WO.RC: 10; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 11; NM.Case.N: 0110; NM.Case.Pn: 0100 Middle English; A.N.PPr: 1111; A.N.Pst: 1111; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 00000; NM.Def: 10010; NM.Gen: 0000; T.Fut: 10000; VM.PPr.A: 000; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 000; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 01; WO.MC: 0100; WO.Poss: 01; WO.Adj: 10; WO.RC: 10; WO.Ptc: 01; WO.Sub: 0100; WO.WH: 11; NM.Case.N: 0100; NM.Case.Pn: 0100 Middle Greek; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 11001; NM.Def: 01010; NM.Gen: 0011; T.Fut: 10110; VM.PPr.A: 100; VM.PPr.D: 000; VM.PPr.O: 000; VM.Pst.A: 100; VM.Pst.O: 000; WO.Adp: 01; WO.Cl.Fin: 011; WO.Cl.Inf: 011; WO.Cl.Ptc: 011; WO.Inf: 11; WO.MC: 0100; WO.Poss: 11; WO.Adj: 11; WO.RC: 10; WO.Ptc: 11; WO.Sub: 0100; WO.WH: 01; NM.Case.N: 0110; NM.Case.Pn: 0100 Middle High German; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 11001; NM.Def: 10010; NM.Gen: 0011; T.Fut: 10000; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 000; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 0010; WO.Poss: 01; WO.Adj: 10; WO.RC: 10; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 11; NM.Case.N: 0110; NM.Case.Pn: 0110 Middle Irish; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 1111; A.Pn.Pst: 1111; NM.Case: 11001; NM.Def: 00011; NM.Gen: 0010; T.Fut: 00010; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 100; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 010; WO.Cl.Inf: 000; WO.Cl.Ptc: 010; WO.Inf: 00; WO.MC: 0001; WO.Poss: 10; WO.Adj: 01; WO.RC: 10; WO.Ptc: –; WO.Sub: 0001; WO.WH: –; NM.Case.N: 0100; NM.Case.Pn: 0000 Middle Low German; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 11001; NM.Def: 10010; NM.Gen: 0011; T.Fut: 10000; VM.PPr.A: 000; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 000; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 0010; WO.Poss: 11; WO.Adj: 10; WO.RC: 10; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 11; NM.Case.N: 0110; NM.Case.Pn: 0100

419

Middle Persian; A.N.PPr: 1111; A.N.Pst: 1111; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 00000; NM.Def: 00000; NM.Gen: 0000; T.Fut: 10000; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 100; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 100; WO.Cl.Inf: 100; WO.Cl.Ptc: 100; WO.Inf: 10; WO.MC: 1000; WO.Poss: 10; WO.Adj: 01; WO.RC: 10; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 11; NM.Case.N: 0000; NM.Case.Pn: 0000 Middle Welsh; A.N.PPr: 1111; A.N.Pst: 1111; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 00000; NM.Def: –; NM.Gen: 0010; T.Fut: 00000; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 100; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 010; WO.Cl.Inf: 000; WO.Cl.Ptc: –; WO.Inf: 00; WO.MC: 0010; WO.Poss: 10; WO.Adj: 01; WO.RC: 10; WO.Ptc: –; WO.Sub: 0001; WO.WH: –; NM.Case.N: 0000; NM.Case.Pn: 0000 Modern Armenian; A.N.PPr: 1111; A.N.Pst: 1111; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 00011; NM.Def: 00101; NM.Gen: 0000; T.Fut: 01010; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 100; VM.Pst.O: 100; WO.Adp: 11; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 01; WO.MC: 1100; WO.Poss: 10; WO.Adj: 10; WO.RC: 10; WO.Ptc: 11; WO.Sub: 1100; WO.WH: 11; NM.Case.N: 1101; NM.Case.Pn: 0101 Modern Greek; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 11001; NM.Def: 01010; NM.Gen: 0011; T.Fut: 00100; VM.PPr.A: 100; VM.PPr.D: 100; VM.PPr.O: 010; VM.Pst.A: 100; VM.Pst.O: 010; WO.Adp: 01; WO.Cl.Fin: 011; WO.Cl.Inf: 000; WO.Cl.Ptc: 001; WO.Inf: 00; WO.MC: 0100; WO.Poss: 11; WO.Adj: 11; WO.RC: 10; WO.Ptc: 11; WO.Sub: 0100; WO.WH: 01; NM.Case.N: 0110; NM.Case.Pn: 0100 Nepali; A.N.PPr: 0001; A.N.Pst: 0001; A.Pn.PPr: 0011; A.Pn.Pst: 0001; NM.Case: 10001; NM.Def: 00000; NM.Gen: 0000; T.Fut: –; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 100; VM.Pst.O: 100; WO.Adp: 10; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 1000; WO.Poss: 01; WO.Adj: 10; WO.RC: 01; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 10; NM.Case.N: 1111; NM.Case.Pn: 1101 Northern Saami; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 00011; NM.Def: 00000; NM.Gen: 0000; T.Fut: 00000; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 100; VM.Pst.O: 100; WO.Adp: 10; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 11; WO.MC: 0100; WO.Poss: 11; WO.Adj: 10; WO.RC: 10; WO.Ptc: 11; WO.Sub: 0100; WO.WH: 01; NM.Case.N: 1111; NM.Case.Pn: 1101 Norwegian (Bokmål); A.N.PPr: 1111; A.N.Pst: 1111; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 00000; NM.Def: 10001; NM.Gen: 0011; T.Fut: 10000;

420

Appendix 2c: Grammar: State combinations in languages

VM.PPr.A: 001; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 001; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 01; WO.MC: 0010; WO.Poss: 11; WO.Adj: 10; WO.RC: 10; WO.Ptc: 01; WO.Sub: 0100; WO.WH: 11; NM.Case.N: 0000; NM.Case.Pn: 0100 Norwegian (Nynorsk); A.N.PPr: 1111; A.N.Pst: 1111; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 00000; NM.Def: 10001; NM.Gen: 0011; T.Fut: 10000; VM.PPr.A: 001; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 001; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 01; WO.MC: 0010; WO.Poss: 01; WO.Adj: 10; WO.RC: 10; WO.Ptc: 01; WO.Sub: 0100; WO.WH: 11; NM.Case.N: 0000; NM.Case.Pn: 0100 Old Church Slavonic; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 10001; NM.Def: 10000; NM.Gen: 0011; T.Fut: 10001; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 000; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 001; WO.Cl.Inf: 001; WO.Cl.Ptc: 001; WO.Inf: 01; WO.MC: 0100; WO.Poss: 10; WO.Adj: 11; WO.RC: 00; WO.Ptc: 01; WO.Sub: 0100; WO.WH: 01; NM.Case.N: 0111; NM.Case.Pn: 0111 Old Dutch; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 11001; NM.Def: –; NM.Gen: 0011; T.Fut: 10000; VM.PPr.A: 000; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 000; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: –; WO.Inf: –; WO.MC: –; WO.Poss: –; WO.Adj: 10; WO.RC: –; WO.Ptc: –; WO.Sub: –; WO.WH: –; NM.Case.N: 0110; NM.Case.Pn: 0110 Old English; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 11001; NM.Def: 10010; NM.Gen: 0011; T.Fut: 10000; VM.PPr.A: 000; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 000; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 0010; WO.Poss: 01; WO.Adj: 10; WO.RC: 10; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 11; NM.Case.N: 0110; NM.Case.Pn: 0100 Old French; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 11001; NM.Def: 01010; NM.Gen: 0010; T.Fut: 00010; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 100; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 010; WO.Cl.Inf: 001; WO.Cl.Ptc: 010; WO.Inf: 01; WO.MC: 0010; WO.Poss: 10; WO.Adj: 01; WO.RC: 10; WO.Ptc: 01; WO.Sub: 1000; WO.WH: 01; NM.Case.N: 0010; NM.Case.Pn: 0100 Old Frisian; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 11001; NM.Def: 10010; NM.Gen: 0011; T.Fut: –;

VM.PPr.A: 000; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 000; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 001; WO.Cl.Inf: 001; WO.Cl.Ptc: 001; WO.Inf: 10; WO.MC: 0010; WO.Poss: 01; WO.Adj: 10; WO.RC: 10; WO.Ptc: 10; WO.Sub: 1000; WO.WH: –; NM.Case.N: 0110; NM.Case.Pn: 0100 Old Georgian; A.N.PPr: 0011; A.N.Pst: 1010; A.Pn.PPr: 1111; A.Pn.Pst: 1111; NM.Case: 00001; NM.Def: 00000; NM.Gen: 0000; T.Fut: 00001; VM.PPr.A: 100; VM.PPr.D: 100; VM.PPr.O: 010; VM.Pst.A: 100; VM.Pst.O: 010; WO.Adp: 10; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 00; WO.MC: 0100; WO.Poss: 10; WO.Adj: 10; WO.RC: 10; WO.Ptc: 00; WO.Sub: 0100; WO.WH: 10; NM.Case.N: 1111; NM.Case.Pn: 0001 Old High German; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 11001; NM.Def: 10010; NM.Gen: 0011; T.Fut: –; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 000; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 0010; WO.Poss: 01; WO.Adj: 10; WO.RC: 10; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 11; NM.Case.N: 0110; NM.Case.Pn: 0110 Old Irish; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 11001; NM.Def: 00011; NM.Gen: 0011; T.Fut: 00010; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 100; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 010; WO.Cl.Inf: 000; WO.Cl.Ptc: 010; WO.Inf: 00; WO.MC: 0001; WO.Poss: 10; WO.Adj: 01; WO.RC: 10; WO.Ptc: –; WO.Sub: 0001; WO.WH: –; NM.Case.N: 0110; NM.Case.Pn: 0000 Old Italian; A.N.PPr: 1111; A.N.Pst: 1111; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 00000; NM.Def: 01010; NM.Gen: 00101; T.Fut: 10010; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 000; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 010; WO.Cl.Inf: 001; WO.Cl.Ptc: 001; WO.Inf: 01; WO.MC: 0100; WO.Poss: 10; WO.Adj: 11; WO.RC: 10; WO.Ptc: 01; WO.Sub: 0100; WO.WH: 01; NM.Case.N: 0000; NM.Case.Pn: 0100 Old Norse; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 11001; NM.Def: 10001; NM.Gen: 0011; T.Fut: 10000; VM.PPr.A: 000; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 100; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 01; WO.MC: 0010; WO.Poss: 10; WO.Adj: 10; WO.RC: 10; WO.Ptc: 01; WO.Sub: 0010; WO.WH: 11; NM.Case.N: 1110; NM.Case.Pn: 0110 Old Persian; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 10001; NM.Def: 00000; NM.Gen: 0011; T.Fut: 00000; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 100; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 100; WO.Cl.Inf: 100; WO.Cl.Ptc: 100;

Appendix 2c: Grammar: State combinations in languages

WO.Inf: 10; WO.MC: 1000; WO.Poss: 01; WO.Adj: 01; WO.RC: 10; WO.Ptc: 10; WO.Sub: 1000; WO.WH: –; NM.Case.N: 1111; NM.Case.Pn: 0100 Old Portuguese; A.N.PPr: 1111; A.N.Pst: 1111; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 00000; NM.Def: 01010; NM.Gen: 0010; T.Fut: 10010; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 000; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 001; WO.Cl.Inf: 001; WO.Cl.Ptc: 001; WO.Inf: 01; WO.MC: 0100; WO.Poss: 10; WO.Adj: 11; WO.RC: 10; WO.Ptc: 01; WO.Sub: 0100; WO.WH: 01; NM.Case.N: 0000; NM.Case.Pn: 0100 Old Provençal; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 11001; NM.Def: 01010; NM.Gen: 0010; T.Fut: 00010; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 000; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 010; WO.Cl.Inf: 010; WO.Cl.Ptc: 010; WO.Inf: 01; WO.MC: 0010; WO.Poss: 10; WO.Adj: 01; WO.RC: 10; WO.Ptc: 01; WO.Sub: 0100; WO.WH: –; NM.Case.N: 0010; NM.Case.Pn: 0100 Old Prussian; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 11001; NM.Def: 10010; NM.Gen: 0011; T.Fut: 10010; VM.PPr.A: 000; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 000; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 0100; WO.Poss: 01; WO.Adj: 10; WO.RC: 10; WO.Ptc: 10; WO.Sub: 0100; WO.WH: 11; NM.Case.N: 0110; NM.Case.Pn: 0110 Old Russian; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 10001; NM.Def: 10000; NM.Gen: 0011; T.Fut: 10001; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 000; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 100; WO.Cl.Inf: 100; WO.Cl.Ptc: 100; WO.Inf: 01; WO.MC: 0100; WO.Poss: 10; WO.Adj: 10; WO.RC: 10; WO.Ptc: 01; WO.Sub: 0100; WO.WH: –; NM.Case.N: 0111; NM.Case.Pn: 0111 Old Saxon; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 11001; NM.Def: 10010; NM.Gen: 0011; T.Fut: 10000; VM.PPr.A: 000; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 000; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 0010; WO.Poss: 10; WO.Adj: 10; WO.RC: 10; WO.Ptc: –; WO.Sub: 1000; WO.WH: –; NM.Case.N: 0110; NM.Case.Pn: 0110 Old Spanish; A.N.PPr: 1111; A.N.Pst: 1111; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 00000; NM.Def: 01010; NM.Gen: 0010; T.Fut: 10010; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 000; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 010; WO.Cl.Inf: 001; WO.Cl.Ptc: 001; WO.Inf: 01; WO.MC: 0100; WO.Poss: 10; WO.Adj: 01; WO.RC: 10; WO.Ptc: 01;

421

WO.Sub: 0100; WO.WH: 01; NM.Case.N: 0000; NM.Case.Pn: 0110 Old Swedish; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 11001; NM.Def: 10001; NM.Gen: 0011; T.Fut: 10000; VM.PPr.A: 000; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 000; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 001; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 01; WO.MC: 0010; WO.Poss: 01; WO.Adj: 10; WO.RC: 10; WO.Ptc: 01; WO.Sub: 0010; WO.WH: 11; NM.Case.N: 0110; NM.Case.Pn: 0110 Oriya; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: –; NM.Def: 00101; NM.Gen: 0000; T.Fut: 00010; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 100; VM.Pst.O: 100; WO.Adp: 10; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 1000; WO.Poss: 01; WO.Adj: 10; WO.RC: 01; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 11; NM.Case.N: 0110; NM.Case.Pn: 0100 Ossetian (Iron); A.N.PPr: 1111; A.N.Pst: 1111; A.Pn.PPr: 1111; A.Pn.Pst: 1111; NM.Case: 00011; NM.Def: 00000; NM.Gen: 0000; T.Fut: 01111; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 100; VM.Pst.O: 100; WO.Adp: 10; WO.Cl.Fin: 100; WO.Cl.Inf: 100; WO.Cl.Ptc: 100; WO.Inf: 10; WO.MC: 1000; WO.Poss: 01; WO.Adj: 10; WO.RC: 01; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 01; NM.Case.N: 1101; NM.Case.Pn: 1011 Pali; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 11001; NM.Def: 00000; NM.Gen: 0011; T.Fut: –; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 100; VM.Pst.O: 100; WO.Adp: 10; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 1000; WO.Poss: 01; WO.Adj: 10; WO.RC: –; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 01; NM.Case.N: 0111; NM.Case.Pn: 0111 Parachi; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: –; A.Pn.Pst: 0001; NM.Case: 00011; NM.Def: 00000; NM.Gen: 0000; T.Fut: 00100; VM.PPr.A: 000; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 001; VM.Pst.O: 100; WO.Adp: 11; WO.Cl.Fin: 011; WO.Cl.Inf: 010; WO.Cl.Ptc: 010; WO.Inf: 10; WO.MC: 1000; WO.Poss: 01; WO.Adj: 10; WO.RC: 10; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 00; NM.Case.N: 0111; NM.Case.Pn: 1110 Pashto; A.N.PPr: 1111; A.N.Pst: 1001; A.Pn.PPr: 1111; A.Pn.Pst: 1001; NM.Case: 10001; NM.Def: 00000; NM.Gen: 0110; T.Fut: 00100; VM.PPr.A: 010; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 001; VM.Pst.O: 011; WO.Adp: 11; WO.Cl.Fin: 100; WO.Cl.Inf: 100; WO.Cl.Ptc: 100; WO.Inf: 10; WO.MC: 1000; WO.Poss: 01; WO.Adj: 10; WO.RC: 10; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 00; NM.Case.N: 1001; NM.Case.Pn: 0001 Persian; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 10011; NM.Def: 10101;

422

Appendix 2c: Grammar: State combinations in languages

NM.Gen: 0000; T.Fut: 10000; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 100; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 1000; WO.Poss: 10; WO.Adj: 01; WO.RC: 10; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 11; NM.Case.N: 0010; NM.Case.Pn: 0110 Polish; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 10001; NM.Def: 00000; NM.Gen: 0011; T.Fut: 10001; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 110; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 01; WO.MC: 0100; WO.Poss: 10; WO.Adj: 11; WO.RC: 10; WO.Ptc: 01; WO.Sub: 0100; WO.WH: 00; NM.Case.N: 0111; NM.Case.Pn: 0111 Portuguese; A.N.PPr: 1111; A.N.Pst: 1111; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 00000; NM.Def: 01010; NM.Gen: 0010; T.Fut: 10010; VM.PPr.A: 100; VM.PPr.D: 100; VM.PPr.O: 010; VM.Pst.A: 100; VM.Pst.O: 010; WO.Adp: 01; WO.Cl.Fin: 001; WO.Cl.Inf: 001; WO.Cl.Ptc: 001; WO.Inf: 01; WO.MC: 0100; WO.Poss: 10; WO.Adj: 01; WO.RC: 10; WO.Ptc: 01; WO.Sub: 0100; WO.WH: 01; NM.Case.N: 0000; NM.Case.Pn: 0100 Prakrit; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 11001; NM.Def: 00000; NM.Gen: 0011; T.Fut: 01010; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 100; VM.Pst.O: 100; WO.Adp: 10; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 1000; WO.Poss: 01; WO.Adj: 10; WO.RC: 10; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 01; NM.Case.N: 0111; NM.Case.Pn: 0111 Prasun; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 01001; NM.Def: 00000; NM.Gen: 0010; T.Fut: 01010; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 100; VM.Pst.O: 100; WO.Adp: 10; WO.Cl.Fin: 010; WO.Cl.Inf: 010; WO.Cl.Ptc: 010; WO.Inf: 10; WO.MC: 1000; WO.Poss: 01; WO.Adj: 10; WO.RC: –; WO.Ptc: 10; WO.Sub: –; WO.WH: 00; NM.Case.N: 0010; NM.Case.Pn: 0100 Provençal; A.N.PPr: 1111; A.N.Pst: 1111; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 00000; NM.Def: 01010; NM.Gen: 0010; T.Fut: 00010; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 000; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 010; WO.Cl.Inf: 010; WO.Cl.Ptc: 010; WO.Inf: 01; WO.MC: 0100; WO.Poss: 10; WO.Adj: 01; WO.RC: 10; WO.Ptc: 01; WO.Sub: 0100; WO.WH: 11; NM.Case.N: 0000; NM.Case.Pn: 0100 Punjabi; A.N.PPr: 0011; A.N.Pst: 1001; A.Pn.PPr: 0011; A.Pn.Pst: 1001; NM.Case: –; NM.Def: 00000; NM.Gen: 0010; T.Fut: 00010; VM.PPr.A: 010; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 001; VM.Pst.O: 001; WO.Adp: 10; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 1000; WO.Poss: 01; WO.Adj: 10;

WO.RC: 11; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 00; NM.Case.N: 1111; NM.Case.Pn: 1101 Romani (Arli); A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 11001; NM.Def: 01010; NM.Gen: 0010; T.Fut: 00100; VM.PPr.A: 000; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 100; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 001; WO.Cl.Inf: 001; WO.Cl.Ptc: 001; WO.Inf: 01; WO.MC: 0100; WO.Poss: –; WO.Adj: 10; WO.RC: 10; WO.Ptc: 01; WO.Sub: 0100; WO.WH: –; NM.Case.N: 1111; NM.Case.Pn: – Romani (Bugurdži); A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 11001; NM.Def: 01010; NM.Gen: 0010; T.Fut: 00100; VM.PPr.A: 000; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 100; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: –; WO.MC: 0100; WO.Poss: 01; WO.Adj: 10; WO.RC: 10; WO.Ptc: 01; WO.Sub: 0100; WO.WH: 01; NM.Case.N: 1111; NM.Case.Pn: 1111 Romani (Burgenland); A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 11001; NM.Def: 01010; NM.Gen: 0010; T.Fut: 00010; VM.PPr.A: 000; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 100; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 1000; WO.Poss: 01; WO.Adj: 10; WO.RC: 10; WO.Ptc: –; WO.Sub: 1000; WO.WH: 01; NM.Case.N: 1111; NM.Case.Pn: 1111 Romani (Kale); A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: –; NM.Def: 00000; NM.Gen: 0000; T.Fut: 00010; VM.PPr.A: 000; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 100; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 01; WO.MC: 0100; WO.Poss: 01; WO.Adj: 10; WO.RC: 10; WO.Ptc: –; WO.Sub: 0100; WO.WH: 01; NM.Case.N: 1111; NM.Case.Pn: 1111 Romani (Kelderash); A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 11001; NM.Def: 01010; NM.Gen: 0010; T.Fut: 00110; VM.PPr.A: 000; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 000; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: –; WO.MC: 0100; WO.Poss: 01; WO.Adj: 10; WO.RC: 10; WO.Ptc: 10; WO.Sub: 0100; WO.WH: 01; NM.Case.N: 1111; NM.Case.Pn: 1111 Romani (Lovara); A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 11001; NM.Def: 01010; NM.Gen: 0010; T.Fut: 00010; VM.PPr.A: 000; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 000; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: –; WO.Cl.Inf: –; WO.Cl.Ptc: –; WO.Inf: –; WO.MC: 0100; WO.Poss: 01; WO.Adj: 10; WO.RC: 10; WO.Ptc: 01; WO.Sub: 0100; WO.WH: 01; NM.Case.N: 1111; NM.Case.Pn: 1111

Appendix 2c: Grammar: State combinations in languages

Romani (Sepečides); A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 11001; NM.Def: 01010; NM.Gen: 0010; T.Fut: 00100; VM.PPr.A: 000; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 100; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: –; WO.MC: 0100; WO.Poss: 01; WO.Adj: 10; WO.RC: 10; WO.Ptc: 01; WO.Sub: 0001; WO.WH: 01; NM.Case.N: 1111; NM.Case.Pn: 1111 Romani (Sinte); A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 11001; NM.Def: 01010; NM.Gen: 0010; T.Fut: –; VM.PPr.A: 000; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 010; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 001; WO.Cl.Inf: 001; WO.Cl.Ptc: 001; WO.Inf: 11; WO.MC: 0010; WO.Poss: 01; WO.Adj: 10; WO.RC: 10; WO.Ptc: 01; WO.Sub: 0100; WO.WH: 01; NM.Case.N: 1111; NM.Case.Pn: 1111 Romanian; A.N.PPr: 1111; A.N.Pst: 1111; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 11001; NM.Def: 01000; NM.Gen: 0011; T.Fut: 10100; VM.PPr.A: 000; VM.PPr.D: 100; VM.PPr.O: 010; VM.Pst.A: 000; VM.Pst.O: 010; WO.Adp: 01; WO.Cl.Fin: 010; WO.Cl.Inf: –; WO.Cl.Ptc: 011; WO.Inf: 01; WO.MC: 0100; WO.Poss: 10; WO.Adj: 01; WO.RC: 10; WO.Ptc: 01; WO.Sub: 0100; WO.WH: 11; NM.Case.N: 1100; NM.Case.Pn: 0110 Romansh; A.N.PPr: 1111; A.N.Pst: 1111; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 00000; NM.Def: 01010; NM.Gen: 0010; T.Fut: 10010; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 000; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 001; WO.Cl.Inf: 010; WO.Cl.Ptc: 010; WO.Inf: 01; WO.MC: 0010; WO.Poss: 10; WO.Adj: 01; WO.RC: 10; WO.Ptc: 01; WO.Sub: 0100; WO.WH: 11; NM.Case.N: 0000; NM.Case.Pn: 0100 Russian; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 10001; NM.Def: 00000; NM.Gen: 0011; T.Fut: 10001; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 010; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 01; WO.MC: 0100; WO.Poss: 10; WO.Adj: 10; WO.RC: 10; WO.Ptc: 01; WO.Sub: 0100; WO.WH: 00; NM.Case.N: 0111; NM.Case.Pn: 0111 Sanskrit; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 11001; NM.Def: 00000; NM.Gen: 0011; T.Fut: 11010; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 100; VM.Pst.O: 100; WO.Adp: 10; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 1000; WO.Poss: 01; WO.Adj: 10; WO.RC: 01; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 01; NM.Case.N: 0111; NM.Case.Pn: 0111 Sardinian; A.N.PPr: 1111; A.N.Pst: 1111; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 00000; NM.Def: 01010; NM.Gen: 0010; T.Fut: 10000; VM.PPr.A: 100;

423

VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 100; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 010; WO.Cl.Inf: 010; WO.Cl.Ptc: 010; WO.Inf: 01; WO.MC: 0100; WO.Poss: 10; WO.Adj: 01; WO.RC: 10; WO.Ptc: 01; WO.Sub: 0100; WO.WH: 01; NM.Case.N: 0000; NM.Case.Pn: 0100 Scandoromani; A.N.PPr: 1111; A.N.Pst: 1111; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 00011; NM.Def: 10001; NM.Gen: 0011; T.Fut: 10000; VM.PPr.A: 001; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 001; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 001; WO.Cl.Inf: –; WO.Cl.Ptc: –; WO.Inf: 01; WO.MC: 0010; WO.Poss: 01; WO.Adj: 10; WO.RC: 10; WO.Ptc: 01; WO.Sub: 0100; WO.WH: 01; NM.Case.N: 0100; NM.Case.Pn: 0100 Scottish Gaelic; A.N.PPr: 0011; A.N.Pst: 1111; A.Pn.PPr: 0011; A.Pn.Pst: 1111; NM.Case: 11001; NM.Def: 00011; NM.Gen: 0010; T.Fut: 00010; VM.PPr.A: 001; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 001; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 0001; WO.Poss: 10; WO.Adj: 01; WO.RC: 10; WO.Ptc: 01; WO.Sub: 0001; WO.WH: 11; NM.Case.N: 0100; NM.Case.Pn: 0000 Serbian; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 10001; NM.Def: 10000; NM.Gen: 0011; T.Fut: 10000; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 110; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 100; WO.Cl.Inf: 100; WO.Cl.Ptc: 100; WO.Inf: 01; WO.MC: 0100; WO.Poss: 10; WO.Adj: 10; WO.RC: 10; WO.Ptc: 01; WO.Sub: 0100; WO.WH: 11; NM.Case.N: 0111; NM.Case.Pn: 0111 Shughni; A.N.PPr: 1111; A.N.Pst: 1111; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 00000; NM.Def: 00000; NM.Gen: 0010; T.Fut: –; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 010; VM.Pst.O: 100; WO.Adp: 11; WO.Cl.Fin: 011; WO.Cl.Inf: 010; WO.Cl.Ptc: 010; WO.Inf: 10; WO.MC: 1000; WO.Poss: 01; WO.Adj: 10; WO.RC: –; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 00; NM.Case.N: 0000; NM.Case.Pn: 1110 Sicilian; A.N.PPr: 1111; A.N.Pst: 1111; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 00000; NM.Def: 01010; NM.Gen: 0010; T.Fut: 00000; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 000; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 010; WO.Cl.Inf: 001; WO.Cl.Ptc: 001; WO.Inf: 01; WO.MC: 0100; WO.Poss: 10; WO.Adj: 11; WO.RC: 10; WO.Ptc: 01; WO.Sub: 0100; WO.WH: 01; NM.Case.N: 0000; NM.Case.Pn: 0100 Sindhi; A.N.PPr: 0011; A.N.Pst: 1001; A.Pn.PPr: 0011; A.Pn.Pst: 1001; NM.Case: 10001; NM.Def: 00000; NM.Gen: 0010; T.Fut: 11010; VM.PPr.A: 110; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 001; VM.Pst.O: 001; WO.Adp: 10; WO.Cl.Fin: 001; WO.Cl.Inf: 001; WO.Cl.Ptc: 001; WO.Inf: 10; WO.MC: 1000; WO.Poss: 01; WO.Adj: 10;

424

Appendix 2c: Grammar: State combinations in languages

WO.RC: 01; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 01; NM.Case.N: 0011; NM.Case.Pn: 1101 Sinhalese; A.N.PPr: 1111; A.N.Pst: 1111; A.Pn.PPr: 1111; A.Pn.Pst: 1111; NM.Case: 00011; NM.Def: 00000; NM.Gen: 0100; T.Fut: 00010; VM.PPr.A: 001; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 001; VM.Pst.O: 100; WO.Adp: 10; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 1000; WO.Poss: 01; WO.Adj: 10; WO.RC: 01; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 00; NM.Case.N: 1101; NM.Case.Pn: 0100 Slovene; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 10001; NM.Def: 10000; NM.Gen: 0011; T.Fut: 10001; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 010; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 100; WO.Cl.Inf: 100; WO.Cl.Ptc: 100; WO.Inf: 01; WO.MC: 0100; WO.Poss: –; WO.Adj: 10; WO.RC: 10; WO.Ptc: 01; WO.Sub: 0100; WO.WH: 01; NM.Case.N: 0111; NM.Case.Pn: 0111 Sogdian; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 10011; NM.Def: 01010; NM.Gen: 0011; T.Fut: 00100; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 100; VM.Pst.O: 100; WO.Adp: 11; WO.Cl.Fin: 100; WO.Cl.Inf: 100; WO.Cl.Ptc: 100; WO.Inf: 10; WO.MC: 1000; WO.Poss: 01; WO.Adj: 10; WO.RC: 10; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 01; NM.Case.N: 0111; NM.Case.Pn: 0100 Spanish; A.N.PPr: 1111; A.N.Pst: 1111; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 00000; NM.Def: 01010; NM.Gen: 0010; T.Fut: 10010; VM.PPr.A: 100; VM.PPr.D: 100; VM.PPr.O: 010; VM.Pst.A: 100; VM.Pst.O: 010; WO.Adp: 01; WO.Cl.Fin: 010; WO.Cl.Inf: 001; WO.Cl.Ptc: 001; WO.Inf: 01; WO.MC: 0100; WO.Poss: 10; WO.Adj: 01; WO.RC: 10; WO.Ptc: 01; WO.Sub: 0100; WO.WH: 10; NM.Case.N: 0000; NM.Case.Pn: 0100 Svan; A.N.PPr: 0011; A.N.Pst: 1010; A.Pn.PPr: 1111; A.Pn.Pst: 1111; NM.Case: 00001; NM.Def: 00000; NM.Gen: –; T.Fut: 00001; VM.PPr.A: 100; VM.PPr.D: 100; VM.PPr.O: 010; VM.Pst.A: 100; VM.Pst.O: 010; WO.Adp: 10; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 00; WO.MC: 1000; WO.Poss: 01; WO.Adj: 10; WO.RC: 10; WO.Ptc: 00; WO.Sub: 1000; WO.WH: 10; NM.Case.N: –; NM.Case.Pn: 0001 Swedish; A.N.PPr: 1111; A.N.Pst: 1111; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 00000; NM.Def: 10001; NM.Gen: 0001; T.Fut: 10000; VM.PPr.A: 001; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 001; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 01; WO.MC: 0010; WO.Poss: 01; WO.Adj: 10; WO.RC: 10; WO.Ptc: 01; WO.Sub: 0100; WO.WH: 11; NM.Case.N: 0000; NM.Case.Pn: 0100 Swiss German; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 11000; NM.Def: 10010; NM.Gen: 0011; T.Fut: 00100; VM.PPr.A: 000; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 001; VM.Pst.O: 100; WO.Adp: 01;

WO.Cl.Fin: 001; WO.Cl.Inf: 010; WO.Cl.Ptc: 010; WO.Inf: 10; WO.MC: 0010; WO.Poss: 01; WO.Adj: 10; WO.RC: 10; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 11; NM.Case.N: 0100; NM.Case.Pn: 0110 Tajik; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 00001; NM.Def: 01001; NM.Gen: 0000; T.Fut: 01000; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 100; VM.Pst.O: 000; WO.Adp: 01; WO.Cl.Fin: 001; WO.Cl.Inf: 010; WO.Cl.Ptc: 010; WO.Inf: 10; WO.MC: 1000; WO.Poss: 01; WO.Adj: 01; WO.RC: 10; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 01; NM.Case.N: 0110; NM.Case.Pn: 0110 Talysh; A.N.PPr: 0011; A.N.Pst: 1001; A.Pn.PPr: 0011; A.Pn.Pst: 1001; NM.Case: 00011; NM.Def: 00000; NM.Gen: 0000; T.Fut: 00100; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 001; VM.Pst.O: 010; WO.Adp: 11; WO.Cl.Fin: 010; WO.Cl.Inf: 010; WO.Cl.Ptc: 010; WO.Inf: 10; WO.MC: 1000; WO.Poss: 01; WO.Adj: 10; WO.RC: 10; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 10; NM.Case.N: 0011; NM.Case.Pn: 0101 Tocharian A; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 10001; NM.Def: 00000; NM.Gen: 0010; T.Fut: 11000; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 100; VM.Pst.O: 100; WO.Adp: 10; WO.Cl.Fin: 001; WO.Cl.Inf: 001; WO.Cl.Ptc: 001; WO.Inf: 10; WO.MC: 1000; WO.Poss: 01; WO.Adj: 10; WO.RC: –; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 01; NM.Case.N: 1111; NM.Case.Pn: 0100 Tocharian B; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 10001; NM.Def: 00000; NM.Gen: 0010; T.Fut: 11000; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 100; VM.Pst.O: 100; WO.Adp: 10; WO.Cl.Fin: 001; WO.Cl.Inf: 001; WO.Cl.Ptc: 001; WO.Inf: 10; WO.MC: 1000; WO.Poss: 01; WO.Adj: 10; WO.RC: –; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 01; NM.Case.N: 1111; NM.Case.Pn: 0100 Turkish; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 00011; NM.Def: 00001; NM.Gen: 0000; T.Fut: 00010; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 100; VM.Pst.O: 100; WO.Adp: 10; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 1000; WO.Poss: 01; WO.Adj: 10; WO.RC: 01; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 10; NM.Case.N: 1111; NM.Case.Pn: 1111 Turkmen; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 00011; NM.Def: 00001; NM.Gen: 0000; T.Fut: 00010; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 100; VM.Pst.O: 100; WO.Adp: 10; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 1000; WO.Poss: 01; WO.Adj: 10; WO.RC: –; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 10; NM.Case.N: 1111; NM.Case.Pn: 1111

Appendix 2c: Grammar: State combinations in languages

Ukrainian; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 10001; NM.Def: 00000; NM.Gen: 0011; T.Fut: 10011; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 010; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 01; WO.MC: 0100; WO.Poss: 10; WO.Adj: 10; WO.RC: 10; WO.Ptc: 01; WO.Sub: 0100; WO.WH: 01; NM.Case.N: 0111; NM.Case.Pn: 0111 Upper Sorbian; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 10001; NM.Def: 00000; NM.Gen: 0011; T.Fut: 10001; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 010; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 0100; WO.Poss: 01; WO.Adj: 10; WO.RC: 10; WO.Ptc: 10; WO.Sub: 0100; WO.WH: 11; NM.Case.N: 0111; NM.Case.Pn: 0111 Urdu; A.N.PPr: 0011; A.N.Pst: 1001; A.Pn.PPr: 0011; A.Pn.Pst: 1001; NM.Case: 00001; NM.Def: 00000; NM.Gen: 0010; T.Fut: 00010; VM.PPr.A: 000; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 001; VM.Pst.O: 001; WO.Adp: 10; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 1000; WO.Poss: 01; WO.Adj: 10; WO.RC: 01; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 10; NM.Case.N: –; NM.Case.Pn: 0110 Uyghur; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 00011; NM.Def: 00001; NM.Gen: 0000; T.Fut: 00010; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 100; VM.Pst.O: 100; WO.Adp: 10; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 1000; WO.Poss: 01; WO.Adj: 10; WO.RC: –; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 10; NM.Case.N: 1111; NM.Case.Pn: 1111 Uzbek; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 00011; NM.Def: 00001; NM.Gen: 0000; T.Fut: 00010; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 100; VM.Pst.O: 100; WO.Adp: 10; WO.Cl.Fin: 000;

425

WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 1000; WO.Poss: 01; WO.Adj: 10; WO.RC: –; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 10; NM.Case.N: 1111; NM.Case.Pn: 1111 Wakhi; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 01001; NM.Def: 01010; NM.Gen: 0000; T.Fut: 00000; VM.PPr.A: 000; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 000; VM.Pst.O: 100; WO.Adp: 11; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 10; WO.MC: 1000; WO.Poss: 01; WO.Adj: 10; WO.RC: 10; WO.Ptc: 10; WO.Sub: 1000; WO.WH: 00; NM.Case.N: 1111; NM.Case.Pn: 1111 Walloon; A.N.PPr: 1111; A.N.Pst: 1111; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 00000; NM.Def: 01010; NM.Gen: 0010; T.Fut: 10010; VM.PPr.A: 000; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 000; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 010; WO.Cl.Inf: 010; WO.Cl.Ptc: 010; WO.Inf: 01; WO.MC: 0100; WO.Poss: 10; WO.Adj: 10; WO.RC: 10; WO.Ptc: 01; WO.Sub: 0100; WO.WH: 01; NM.Case.N: 0000; NM.Case.Pn: 0100 Welsh; A.N.PPr: 1111; A.N.Pst: 1111; A.Pn.PPr: 1111; A.Pn.Pst: 1111; NM.Case: 00000; NM.Def: 00011; NM.Gen: 0010; T.Fut: 10010; VM.PPr.A: 100; VM.PPr.D: 001; VM.PPr.O: 010; VM.Pst.A: 000; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 000; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 01; WO.MC: 0001; WO.Poss: 10; WO.Adj: 01; WO.RC: 10; WO.Ptc: 01; WO.Sub: 0001; WO.WH: 11; NM.Case.N: 0000; NM.Case.Pn: 0000 Yiddish; A.N.PPr: 0011; A.N.Pst: 0011; A.Pn.PPr: 0011; A.Pn.Pst: 0011; NM.Case: 11000; NM.Def: 10010; NM.Gen: 0011; T.Fut: 10000; VM.PPr.A: 000; VM.PPr.D: 001; VM.PPr.O: 100; VM.Pst.A: 000; VM.Pst.O: 100; WO.Adp: 01; WO.Cl.Fin: 001; WO.Cl.Inf: 000; WO.Cl.Ptc: 000; WO.Inf: 01; WO.MC: 0010; WO.Poss: 01; WO.Adj: 10; WO.RC: 10; WO.Ptc: 01; WO.Sub: 0010; WO.WH: 11; NM.Case.N: 0110; NM.Case.Pn: 0110

Appendix 2d: Grammar: Solutions 1–10 by Structure This appendix gives the percentages of the 10 clusters retrieved by the Structure analysis described in 5.7.1 of the book, forming the basis for maps 27ab.

Language Name

1

2

3

4

5

6

7

8

9

10

Albanian (Tosk)

 0.1 %

 0.2 %

 0.7 %

64.9 %

 0.8 %

 0.2 %

 0.5 %

 0.3 %

 1.7 %

30.5 %

Angloromani

 0.2 %

 0.2 %

 1.4 %

 0.2 %

 0.1 %

 6.6 %

 0.2 %

88.2 %

 2.3 %

 0.8 %

Ashkun

 0.4 %

96.4 %

 0.3 %

 0.1 %

 0.3 %

 0.2 %

 1.6 %

 0.3 %

 0.2 %

 0.2 %

Assamese

 0.2 %

 1.4 %

 0.1 %

 0.2 %

 0.7 %

 0.1 %

96.6 %

 0.1 %

 0.1 %

 0.5 %

Avestan

 0.4 %

 0.1 %

 0.1 %

 0.1 %

98.1 %

 0.2 %

 0.3 %

 0.1 %

 0.1 %

 0.4 %

Baluchi

 1.0 %

 0.2 %

 0.2 %

 0.2 %

 2.3 %

 0.1 %

95.0 %

 0.5 %

 0.2 %

 0.2 %

Basque (East)

 0.2 %

37.9 %

56.8 %

 0.1 %

 0.5 %

 0.2 %

 3.7 %

 0.1 %

 0.2 %

 0.2 %

Basque (West)

 0.2 %

 1.5 %

90.2 %

 0.3 %

 1.1 %

 0.2 %

 5.9 %

 0.1 %

 0.2 %

 0.3 %

Batsbi

 0.4 %

 8.0 %

88.6 %

 0.1 %

 0.5 %

 0.4 %

 1.0 %

 0.3 %

 0.3 %

 0.3 %

Bengali

 0.1 %

 0.2 %

 0.2 %

 0.1 %

 0.2 %

 0.1 %

98.7 %

 0.2 %

 0.1 %

 0.1 %

Breton

 0.2 %

 0.1 %

 0.1 %

 0.1 %

 0.1 %

97.4 %

 0.1 %

 0.9 %

 0.9 %

 0.1 %

Bulgarian

 0.9 %

 0.8 %

 0.2 %

 1.4 %

 1.0 %

 0.4 %

 0.4 %

11.1 %

77.4 %

 6.5 %

Catalan

 0.1 %

 0.1 %

 0.1 %

 0.1 %

 0.1 %

 0.3 %

 0.1 %

 0.2 %

98.6 %

 0.2 %

Classical Greek

 1.4 %

 0.3 %

 0.2 %

81.5 %

14.7 %

 0.4 %

 0.6 %

 0.2 %

 0.2 %

 0.5 %

Cornish

 0.6 %

 0.2 %

 0.3 %

 0.2 %

 0.4 %

89.5 %

 0.3 %

 5.0 %

 3.3 %

 0.2 %

Croatian

 0.3 %

 0.2 %

 0.1 %

 0.2 %

 0.2 %

 0.1 %

 0.1 %

 0.3 %

 0.2 %

98.3 %

Czech

 0.6 %

 0.1 %

 0.1 %

 3.2 %

 0.5 %

 0.3 %

 0.1 %

 0.3 %

 0.9 %

93.9 %

Danish

 0.3 %

 0.1 %

 0.1 %

 0.1 %

 0.1 %

 0.2 %

 0.1 %

98.5 %

 0.3 %

 0.1 %

Dutch

23.7 %

 0.8 %

 0.2 %

 0.2 %

 1.2 %

 0.2 %

 0.4 %

71.3 %

 1.8 %

 0.1 %

Elfdalian

97.5 %

 0.2 %

 0.1 %

 0.4 %

 0.3 %

 0.2 %

 0.2 %

 0.6 %

 0.2 %

 0.4 %

English

 0.2 %

 0.2 %

 0.2 %

 0.2 %

 0.2 %

 0.1 %

 0.2 %

84.4 %

14.0 %

 0.3 %

Estonian

 0.3 %

 0.9 %

 0.3 %

 0.1 %

 2.5 %

 0.2 %

34.3 %

 0.3 %

 0.2 %

60.9 %

Faroese

96.0 %

 0.2 %

 0.1 %

 0.1 %

 0.1 %

 0.2 %

 0.1 %

 1.3 %

 0.2 %

 1.6 %

Finnish

 0.2 %

 0.3 %

 0.6 %

 0.1 %

 2.4 %

 0.1 %

 2.7 %

 0.3 %

 0.3 %

93.0 %

French

 0.2 %

 0.1 %

 0.1 %

 0.1 %

 0.1 %

 0.2 %

 0.1 %

 0.3 %

98.6 %

 0.2 %

Frisian

40.4 %

 0.5 %

 0.1 %

 0.2 %

 0.3 %

 0.7 %

 0.4 %

56.9 %

 0.3 %

 0.3 %

Friulian

 0.2 %

 0.2 %

 0.1 %

 0.1 %

 0.2 %

 0.2 %

 0.1 %

 0.3 %

98.1 %

 0.4 %

Georgian

 0.1 %

 0.2 %

98.8 %

 0.1 %

 0.1 %

 0.1 %

 0.3 %

 0.1 %

 0.1 %

 0.2 %

German

98.7 %

 0.1 %

 0.1 %

 0.1 %

 0.2 %

 0.1 %

 0.2 %

 0.1 %

 0.2 %

 0.2 %

Gilaki

 1.3 %

 0.1 %

 0.1 %

 0.1 %

 0.8 %

 0.3 %

95.8 %

 0.6 %

 0.4 %

 0.6 %

Gothic

91.7 %

 0.2 %

 0.1 %

 0.5 %

 4.9 %

 0.3 %

 0.5 %

 0.2 %

 0.8 %

 0.7 %

Gujarati

 0.2 %

98.3 %

 0.1 %

 0.1 %

 0.2 %

 0.1 %

 0.6 %

 0.1 %

 0.1 %

 0.2 %

Hindi

 0.4 %

97.2 %

 0.1 %

 0.1 %

 1.2 %

 0.2 %

 0.2 %

 0.1 %

 0.2 %

 0.2 %

Hittite

 0.5 %

 0.4 %

 0.1 %

 0.1 %

97.3 %

 0.1 %

 1.2 %

 0.2 %

 0.1 %

 0.1 %

Hungarian

 0.3 %

 0.6 %

 0.4 %

 0.2 %

 0.4 %

 0.1 %

56.5 %

 1.1 %

 3.2 %

36.9 %

Icelandic

97.5 %

 0.1 %

 0.1 %

 0.1 %

 0.1 %

 0.2 %

 0.1 %

 0.5 %

 0.3 %

 0.9 %

Irish

 0.7 %

 0.2 %

 0.1 %

 0.2 %

 0.3 %

97.2 %

 0.3 %

 0.2 %

 0.3 %

 0.5 %

Italian

 0.2 %

 0.1 %

 0.1 %

 0.2 %

 0.1 %

 0.2 %

 0.1 %

 0.2 %

98.8 %

 0.1 %

Kabardian

 0.1 %

 0.9 %

97.3 %

 0.1 %

 0.2 %

 0.3 %

 0.5 %

 0.2 %

 0.3 %

 0.1 %

Karachay-Balkar

 0.1 %

 0.1 %

 0.1 %

 0.1 %

 0.3 %

 0.1 %

98.9 %

 0.1 %

 0.1 %

 0.1 %

https://doi.org/10.1515/9783110367416-013

427

Appendix 2d: Grammar: Solutions 1–10 by Structure

Language Name

1

2

3

4

5

6

7

8

9

10

Kashmiri

 0.9 %

95.6 %

 0.2 %

 0.2 %

 0.3 %

 0.4 %

 0.4 %

 1.0 %

 0.5 %

 0.3 %

Kati

 0.1 %

97.9 %

 0.4 %

 0.1 %

 0.3 %

 0.1 %

 0.5 %

 0.1 %

 0.2 %

 0.2 %

Kazakh

 0.1 %

 0.2 %

 0.1 %

 0.1 %

 0.3 %

 0.1 %

98.4 %

 0.1 %

 0.1 %

 0.3 %

Khowar

 2.0 %

 2.0 %

 0.2 %

 0.4 %

 2.0 %

 0.4 %

90.7 %

 0.6 %

 1.3 %

 0.3 %

Khwarshi

 0.3 %

95.1 %

 1.7 %

 0.3 %

 1.0 %

 0.1 %

 0.9 %

 0.4 %

 0.1 %

 0.2 %

Konkani

 0.1 %

98.5 %

 0.2 %

 0.1 %

 0.3 %

 0.1 %

 0.5 %

 0.2 %

 0.1 %

 0.1 %

Kryz

 0.1 %

72.3 %

26.0 %

 0.1 %

 0.1 %

 0.4 %

 0.3 %

 0.2 %

 0.1 %

 0.2 %

Kurdish (Kurmanji)

 6.4 %

70.5 %

 0.3 %

 1.4 %

 0.7 %

 9.1 %

 0.2 %

 1.0 %

10.1 %

 0.2 %

Kurdish (Sorani)

 2.0 %

43.3 %

 0.9 %

 0.6 %

 1.5 %

18.3 %

 1.2 %

 1.8 %

30.4 %

 0.1 %

Ladin

 0.2 %

 0.1 %

 0.1 %

 0.1 %

 0.1 %

 0.2 %

 0.1 %

 0.5 %

98.4 %

 0.1 %

Latin

 5.6 %

 0.1 %

 0.1 %

 0.6 %

89.3 %

 1.6 %

 0.2 %

 0.2 %

 0.9 %

 1.5 %

Latvian

 0.1 %

 0.1 %

 0.2 %

 0.1 %

 0.3 %

 0.2 %

 0.3 %

 0.2 %

 0.2 %

98.3 %

Laz

 0.2 %

 0.2 %

98.5 %

 0.1 %

 0.2 %

 0.1 %

 0.3 %

 0.1 %

 0.1 %

 0.1 %

Lezgian

 0.5 %

31.9 %

31.8 %

 0.2 %

 0.9 %

 0.5 %

32.7 %

 1.1 %

 0.2 %

 0.3 %

Lithuanian

 1.5 %

 0.4 %

 0.1 %

 0.1 %

 0.9 %

 0.2 %

 0.5 %

 0.2 %

 0.2 %

95.9 %

Low German

98.3 %

 0.1 %

 0.1 %

 0.1 %

 0.2 %

 0.2 %

 0.2 %

 0.4 %

 0.3 %

 0.1 %

Luwian

 0.3 %

 0.4 %

 0.3 %

 0.1 %

95.8 %

 0.1 %

 2.6 %

 0.1 %

 0.1 %

 0.2 %

Maithili

 0.3 %

 2.7 %

 1.7 %

 0.8 %

 0.3 %

 0.2 %

93.5 %

 0.2 %

 0.1 %

 0.3 %

Maldivian

 0.1 %

 1.4 %

31.6 %

 0.1 %

 0.4 %

 0.4 %

62.5 %

 2.9 %

 0.3 %

 0.2 %

Manx

 0.2 %

 0.1 %

 0.2 %

 0.1 %

 0.1 %

98.3 %

 0.1 %

 0.4 %

 0.4 %

 0.1 %

Marathi

 0.2 %

98.3 %

 0.2 %

 0.1 %

 0.2 %

 0.1 %

 0.4 %

 0.1 %

 0.1 %

 0.2 %

Megrelian

 0.2 %

 0.4 %

97.7 %

 0.1 %

 0.4 %

 0.1 %

 0.7 %

 0.2 %

 0.1 %

 0.1 %

Middle Breton

 0.4 %

 0.3 %

 0.1 %

 0.2 %

 0.2 %

24.1 %

 0.3 %

 0.6 %

73.4 %

 0.3 %

Middle Dutch

98.4 %

 0.1 %

 0.1 %

 0.2 %

 0.4 %

 0.3 %

 0.1 %

 0.2 %

 0.1 %

 0.1 %

Middle English

 1.1 %

 0.1 %

 0.1 %

 0.2 %

 0.2 %

 0.4 %

 0.3 %

92.6 %

 4.1 %

 1.0 %

Middle Greek

 1.5 %

 0.2 %

 0.1 %

94.6 %

 0.5 %

 0.2 %

 0.1 %

 0.4 %

 2.2 %

 0.3 %

Middle High German

98.1 %

 0.2 %

 0.1 %

 0.2 %

 0.5 %

 0.1 %

 0.2 %

 0.2 %

 0.1 %

 0.4 %

Middle Irish

 0.8 %

 0.3 %

 0.2 %

 0.6 %

 0.4 %

96.8 %

 0.3 %

 0.1 %

 0.2 %

 0.3 %

Middle Low German

98.6 %

 0.1 %

 0.1 %

 0.2 %

 0.2 %

 0.2 %

 0.2 %

 0.2 %

 0.1 %

 0.2 %

Middle Persian

 0.6 %

 0.3 %

 0.5 %

 0.1 %

42.1 %

25.4 %

 0.5 %

 8.8 %

21.5 %

 0.2 %

Middle Welsh

 0.6 %

 0.1 %

 0.2 %

 0.3 %

 0.3 %

51.7 %

 0.2 %

 1.5 %

44.8 %

 0.2 %

Modern Armenian

 0.3 %

 0.3 %

 0.5 %

 0.2 %

 0.4 %

 1.0 %

53.4 %

 1.5 %

41.7 %

 0.6 %

Modern Greek

 0.6 %

 0.1 %

 0.2 %

96.6 %

 0.2 %

 0.3 %

 0.1 %

 0.3 %

 0.4 %

 1.2 %

Nepali

 0.4 %

 5.9 %

 0.5 %

 0.2 %

 2.4 %

 0.2 %

89.2 %

 0.1 %

 0.1 %

 0.9 %

Northern Saami

 0.3 %

 0.1 %

 0.2 %

 0.2 %

 0.2 %

 0.2 %

48.5 %

 0.2 %

 0.2 %

49.9 %

Norwegian (Bokmål)

 0.4 %

 0.1 %

 0.1 %

 0.1 %

 0.1 %

 0.2 %

 0.1 %

98.4 %

 0.3 %

 0.1 %

Norwegian (Nynorsk)  0.4 %

 0.1 %

 0.1 %

 0.1 %

 0.1 %

 0.2 %

 0.1 %

98.6 %

 0.2 %

 0.1 %

Old Church Slavonic

 0.4 %

 0.2 %

 0.1 %

 0.6 %

 0.5 %

 0.2 %

 0.1 %

 0.4 %

 0.4 %

97.2 %

Old Dutch

98.4 %

 0.1 %

 0.1 %

 0.1 %

 0.3 %

 0.2 %

 0.1 %

 0.2 %

 0.2 %

 0.2 %

Old English

98.4 %

 0.1 %

 0.1 %

 0.1 %

 0.2 %

 0.1 %

 0.2 %

 0.2 %

 0.1 %

 0.4 %

Old French

39.1 %

 0.1 %

 0.2 %

 0.3 %

 2.9 %

 2.3 %

 0.2 %

 0.1 %

54.3 %

 0.4 %

Old Frisian

97.3 %

 0.2 %

 0.1 %

 0.5 %

 0.4 %

 0.2 %

 0.3 %

 0.2 %

 0.5 %

 0.4 %

Old Georgian

 0.2 %

 0.1 %

94.8 %

 1.2 %

 0.1 %

 0.5 %

 0.1 %

 0.3 %

 0.7 %

 2.0 %

Old High German

98.1 %

 0.2 %

 0.1 %

 0.1 %

 0.6 %

 0.2 %

 0.3 %

 0.1 %

 0.2 %

 0.2 %

Old Irish

21.2 %

 0.1 %

 0.1 %

 2.2 %

 1.9 %

70.3 %

 0.4 %

 0.2 %

 0.6 %

 2.9 %

428

Appendix 2d: Grammar: Solutions 1–10 by Structure

Language Name

1

2

3

4

5

6

7

8

9

10

Old Italian

 0.2 %

 0.1 %

 0.0 %

 0.2 %

 0.1 %

 0.1 %

 0.2 %

 0.2 %

98.6 %

 0.3 %

Old Norse

95.5 %

 0.1 %

 0.3 %

 0.3 %

 0.2 %

 0.2 %

 0.4 %

 0.3 %

 0.5 %

 2.3 %

Old Persian

 0.5 %

 0.3 %

 0.2 %

 0.2 %

97.4 %

 0.2 %

 0.7 %

 0.2 %

 0.2 %

 0.4 %

Old Portuguese

 0.2 %

 0.1 %

 0.1 %

 0.1 %

 0.1 %

 0.1 %

 0.2 %

 0.4 %

98.4 %

 0.2 %

Old Provençal

36.1 %

 0.1 %

 0.1 %

 2.7 %

 0.1 %

 1.1 %

 0.2 %

 0.2 %

58.8 %

 0.6 %

Old Prussian

82.7 %

 0.2 %

 0.2 %

 0.5 %

 0.4 %

 0.2 %

 0.3 %

 0.4 %

 0.4 %

14.9 %

Old Russian

 0.2 %

 0.1 %

 0.1 %

 0.1 %

 0.2 %

 0.1 %

 0.2 %

 0.2 %

 0.3 %

98.5 %

Old Saxon

98.6 %

 0.2 %

 0.1 %

 0.1 %

 0.2 %

 0.2 %

 0.1 %

 0.2 %

 0.1 %

 0.2 %

Old Spanish

 0.1 %

 0.1 %

 0.1 %

 0.1 %

 0.1 %

 0.2 %

 0.1 %

 0.1 %

98.9 %

 0.2 %

Old Swedish

97.6 %

 0.1 %

 0.1 %

 0.1 %

 0.3 %

 0.2 %

 0.1 %

 0.3 %

 0.2 %

 1.0 %

Oriya

 2.4 %

 0.7 %

 0.4 %

 0.4 %

 3.0 %

 0.6 %

91.4 %

 0.5 %

 0.4 %

 0.2 %

Ossetian (Iron)

 0.2 %

 1.7 %

50.6 %

 0.1 %

45.2 %

 0.3 %

 1.0 %

 0.5 %

 0.2 %

 0.2 %

Pali

 0.5 %

 0.3 %

 0.2 %

 0.2 %

97.6 %

 0.2 %

 0.4 %

 0.1 %

 0.1 %

 0.5 %

Parachi

 3.4 %

38.1 %

 0.2 %

 3.9 %

11.8 %

 0.2 %

40.7 %

 0.3 %

 0.2 %

 1.1 %

Pashto

 0.1 %

93.6 %

 2.1 %

 0.3 %

 0.8 %

 1.1 %

 0.2 %

 1.1 %

 0.3 %

 0.4 %

Persian

55.0 %

 0.2 %

 0.3 %

 0.3 %

 2.5 %

 2.6 %

36.9 %

 0.5 %

 1.3 %

 0.4 %

Polish

 0.3 %

 0.2 %

 0.2 %

 0.2 %

 0.3 %

 0.4 %

 0.3 %

 0.2 %

 0.3 %

97.7 %

Portuguese

 0.2 %

 0.1 %

 0.6 %

 6.2 %

 0.1 %

 0.2 %

 0.1 %

 0.2 %

92.1 %

 0.2 %

Prakrit

 0.4 %

 0.2 %

 0.1 %

 0.1 %

97.7 %

 0.1 %

 0.9 %

 0.1 %

 0.1 %

 0.2 %

Prasun

 0.4 %

 2.4 %

 0.5 %

 0.9 %

76.6 %

 0.9 %

14.6 %

 0.4 %

 3.1 %

 0.2 %

Provençal

 0.1 %

 0.1 %

 0.1 %

 0.1 %

 0.1 %

 0.3 %

 0.1 %

 0.2 %

98.8 %

 0.1 %

Punjabi

 0.1 %

97.8 %

 0.2 %

 0.1 %

 0.2 %

 0.1 %

 1.0 %

 0.1 %

 0.1 %

 0.2 %

Romani (Arli)

 0.5 %

 0.1 %

 0.1 %

 0.8 %

 0.4 %

 0.1 %

 0.1 %

 0.3 %

 0.8 %

96.8 %

Romani (Bugurdži)

 0.3 %

 0.2 %

 0.1 %

 0.3 %

 0.2 %

 0.1 %

 0.4 %

 0.1 %

 0.3 %

98.0 %

Romani (Burgenland)  4.5 %

 2.5 %

 0.1 %

 0.3 %

55.0 %

 0.4 %

15.7 %

 0.2 %

 0.2 %

21.1 %

Romani (Kale)

 0.4 %

 0.3 %

 0.2 %

 0.2 %

 0.3 %

 0.1 %

 1.6 %

 0.2 %

 0.2 %

96.6 %

Romani (Kelderash)

 0.4 %

 0.5 %

 0.2 %

 0.5 %

 2.1 %

 0.3 %

 3.0 %

 0.2 %

 0.1 %

92.7 %

Romani (Lovara)

 0.2 %

 0.2 %

 0.2 %

 0.2 %

 0.2 %

 0.2 %

 0.4 %

 0.2 %

 0.2 %

98.1 %

Romani (Sepečides)

 1.1 %

 0.3 %

 0.2 %

 0.6 %

 1.0 %

 0.7 %

 1.1 %

 0.1 %

 0.3 %

94.5 %

Romani (Sinte)

 6.9 %

 0.3 %

 0.1 %

 0.8 %

 0.8 %

 0.4 %

 0.3 %

 0.4 %

 0.6 %

89.5 %

Romanian

 0.8 %

 0.1 %

 0.2 %

58.6 %

 0.2 %

 0.6 %

 0.1 %

 1.0 %

37.8 %

 0.5 %

Romansh

 0.8 %

 0.1 %

 0.1 %

 0.2 %

 0.1 %

 0.9 %

 0.1 %

 1.4 %

96.2 %

 0.2 %

Russian

 0.3 %

 0.1 %

 0.1 %

 0.1 %

 0.3 %

 0.1 %

 0.1 %

 0.1 %

 0.1 %

98.6 %

Sanskrit

 0.3 %

 1.2 %

 0.1 %

 0.2 %

96.3 %

 0.1 %

 0.9 %

 0.1 %

 0.2 %

 0.5 %

Sardinian

 0.1 %

 0.1 %

 0.1 %

 0.1 %

 0.2 %

 0.2 %

 0.1 %

 0.4 %

98.5 %

 0.3 %

Scandoromani

 0.6 %

 0.3 %

 0.1 %

 0.5 %

 0.5 %

 0.2 %

 0.2 %

96.5 %

 0.3 %

 0.8 %

Scottish Gaelic

 1.2 %

 0.3 %

 0.1 %

 0.2 %

 0.2 %

96.4 %

 0.3 %

 0.8 %

 0.1 %

 0.3 %

Serbian

 0.5 %

 0.1 %

 0.1 %

 0.1 %

 0.2 %

 0.2 %

 0.1 %

 0.4 %

 0.2 %

98.3 %

Shughni

 0.3 %

28.6 %

 0.2 %

 0.7 %

 6.8 %

 0.3 %

16.6 %

 0.7 %

45.3 %

 0.4 %

Sicilian

 0.2 %

 0.1 %

 0.1 %

 0.3 %

 0.1 %

 0.3 %

 0.1 %

 0.1 %

98.7 %

 0.2 %

Sindhi

 0.5 %

91.9 %

 0.1 %

 0.7 %

 5.0 %

 0.2 %

 0.5 %

 0.3 %

 0.5 %

 0.3 %

Sinhalese

 0.1 %

30.4 %

20.0 %

 0.2 %

 0.2 %

 2.6 %

41.6 %

 4.5 %

 0.2 %

 0.1 %

Slovene

 0.3 %

 0.1 %

 0.1 %

 0.1 %

 0.4 %

 0.1 %

 0.1 %

 0.1 %

 0.2 %

98.5 %

Sogdian

 0.7 %

 0.3 %

 0.1 %

 0.2 %

97.2 %

 0.3 %

 0.4 %

 0.1 %

 0.3 %

 0.4 %

Spanish

 0.1 %

 0.1 %

 1.4 %

 2.3 %

 0.1 %

 0.2 %

 0.1 %

 0.1 %

95.4 %

 0.2 %

429

Appendix 2d: Grammar: Solutions 1–10 by Structure

Language Name

1

2

3

4

5

6

7

8

9

10

Svan

 0.1 %

 0.2 %

98.3 %

 0.2 %

 0.2 %

 0.2 %

 0.4 %

 0.1 %

 0.1 %

 0.1 %

Swedish

 0.3 %

 0.1 %

 0.1 %

 0.1 %

 0.1 %

 0.1 %

 0.1 %

98.6 %

 0.3 %

 0.2 %

Swiss German

94.6 %

 0.5 %

 0.1 %

 1.0 %

 0.4 %

 0.8 %

 0.2 %

 1.7 %

 0.2 %

 0.5 %

Tajik

 1.1 %

 0.5 %

 0.4 %

 9.4 %

78.2 %

 2.0 %

 3.9 %

 0.7 %

 2.9 %

 0.8 %

Talysh

 0.4 %

94.3 %

 0.6 %

 0.6 %

 0.7 %

 0.5 %

 1.7 %

 0.3 %

 0.6 %

 0.3 %

Tocharian A

 0.5 %

 0.4 %

 0.2 %

 0.3 %

96.7 %

 0.1 %

 1.0 %

 0.2 %

 0.2 %

 0.4 %

Tocharian B

 0.2 %

 0.4 %

 0.2 %

 0.3 %

97.7 %

 0.2 %

 0.5 %

 0.1 %

 0.2 %

 0.3 %

Turkish

 0.1 %

 0.2 %

 0.1 %

 0.1 %

 0.4 %

 0.1 %

98.7 %

 0.1 %

 0.1 %

 0.1 %

Turkmen

 0.1 %

 0.2 %

 0.2 %

 0.1 %

 0.3 %

 0.1 %

98.8 %

 0.1 %

 0.1 %

 0.2 %

Ukrainian

 0.4 %

 0.1 %

 0.1 %

 0.1 %

 0.3 %

 0.1 %

 0.1 %

 0.2 %

 0.6 %

98.0 %

Upper Sorbian

 4.8 %

 1.7 %

 0.3 %

 0.2 %

 4.8 %

 0.2 %

 2.3 %

 0.3 %

 0.1 %

85.2 %

Urdu

 0.3 %

98.0 %

 0.2 %

 0.1 %

 0.4 %

 0.1 %

 0.4 %

 0.2 %

 0.2 %

 0.1 %

Uyghur

 0.1 %

 0.1 %

 0.1 %

 0.1 %

 0.4 %

 0.1 %

98.7 %

 0.1 %

 0.1 %

 0.1 %

Uzbek

 0.1 %

 0.5 %

 0.1 %

 0.1 %

 0.3 %

 0.1 %

98.5 %

 0.1 %

 0.1 %

 0.1 %

Wakhi

 3.2 %

 0.3 %

 0.2 %

 0.5 %

 7.1 %

 0.3 %

87.0 %

 0.3 %

 0.4 %

 0.8 %

Walloon

 0.4 %

 0.1 %

 0.1 %

 0.1 %

 0.1 %

 0.2 %

 0.1 %

 0.4 %

98.2 %

 0.4 %

Welsh

 0.1 %

 0.1 %

 0.2 %

 0.2 %

 0.2 %

97.4 %

 0.1 %

 0.2 %

 1.5 %

 0.1 %

Yiddish

97.7 %

 0.1 %

 0.1 %

 0.1 %

 0.1 %

 0.2 %

 0.1 %

 1.0 %

 0.1 %

 0.4 %

Appendix 3a: Lexicon: list of concepts, coverage by family This appendix lists the complete set of lexical concepts of the lexicon section of the book (chapter 6), organized by the classification system of the database DiACL and divided by family. In the statistical analyses of the book, another system is used. The column SYNONYMS list close synonyms, which are included in the semantic coding described in 6.3.2.

Classification in DiACL Activities

Crops & fruit

Cultural artefacts & tools/ Agricultural tools

ALL

BASQUE

IE

CAUCASUS

SYNONYMS arder, plow

plow

plow

plow (verb)

plow

sew

sew

sew

sew

sow

sow

sow

sow

spin (thread)

spin (thread)

spin (thread)

spin (thread)

twist plait

weave

weave

weave

weave

apple

apple

apple

apple

barley

barley

barley

barley

corn

berry

berry linen

flax

flax

flax

flax

grain (generic)

grain (generic)

grain (generic)

grain (generic)

grape

grape

raisin

corn

grape

grape

lentils

lentils

oats

oats

oats

oats

rye

rye

rye

rye

turnip

turnip

turnip

turnip

beet

wheat

wheat

wheat

wheat

emmer, spelt, corn

axe

(ceramic) pot

(ceramic) pot

axe

axe

axe

(ceramic) pot

axle

axle

axle

cultivated field

cultivated field

cultivated field

flutes

flutes

furrow

furrow

furrow

hub

hub

hub

pasture

pasture

plow (n)

plow (n)

plow (n)

plow

saw

saw

saw

saw

scythe

scythe

scythe

scythe

adze, hatchet, ax axis

cultivated field

farmland, field

ploughshare

pasture arder

mower

sickle

sickle

sickle

sickle

curved knife

spade

spade

spade

spade

hoe, mattock, shovel

wagon

wagon

wagon

wagon

cart, car, carriage, coach, trolley

wheel

wheel

wheel

wheel

yoke

yoke

yoke

yoke

https://doi.org/10.1515/9783110367416-014

Appendix 3a: Lexicon: list of concepts, coverage by family

Classification in DiACL Farm animals

ALL

BASQUE

SYNONYMS honeybee

bee

bee

bee

bee

bull

bull

bull

calf

cat

cat

cat

cat

kitten

cattle (collective term)

cattle (collective term)

cattle

cattle (collective term)

livestock

chicken

chicken

chicken

chicken

poultry, fowl

cow

cow

cow

cow

heifer

dog

dog

dog

dog

bitch, puppy

donkey

donkey

donkey

donkey

ass

duck

duck

duck

duck

drake

goat

goat

goat

goat

kid, buck

hen

hen

hen

hen

horse

horse

horse

horse

kid

Products

CAUCASUS

bull calf

Metals & Materials

IE

431

stallion, mare

kid

lamb

lamb

lamb

lamb

ox

ox

ox

ox

pig

pig

pig

pig

piglet

piglet

piglet

piglet

ram

ram

ram

ram

wether

rooster

rooster

rooster

rooster

cock

sheep (collective term)

sheep (collective term)

sheep

sheep (collective term)

ewe

yearling

yearling

copper

copper

copper

copper

copper

gold

gold

gold

gold

iron

iron

iron

iron

steel

leather

leather

leather

leather

skin

silver

silver

silver

silver

stone

stone

stone

stone

rock, moulder

wood

wood

wood

wood

tree

beeswax

beeswax

wax (bees)

beeswax

fur

fur

fur

fur

animal hair, fleece, pelt

grease

grease

grease

grease

tallow, fat

honey

honey

honey

honey

hops

hops

hops

hops

mead

mead

mead

mead (i.e. based on honey)

meat

meat

meat

meat

milk

milk

milk

milk

swine, sow

flesh

432

Appendix 3a: Lexicon: list of concepts, coverage by family

Classification in DiACL

Seasons

Trees

Weapons etc.

Wild animals

ALL

BASQUE

IE

CAUCASUS

SYNONYMS

salt

salt

salt

salt

wine

wine

wine

wine

wool

wool

wool

wool

fleece

autumn

autumn

autumn

autumn /

fall crop

harvest

harvest

harvest

harvest

spring

spring

spring

spring

summer

summer

summer

summer

hot season, warm season

winter

winter

winter

winter

cold season, rainy season

ash

ash

beech

beech

birch

birch

elm

elm

oak

oak

army

army

army

arrow

arrow

battle axe

battle axe

bow

bow

bow

bow

knife

knife

knife

knife

shield

shield

spear

spear

spear

spear

sword

sword

sword

sword

bear

bear

bear

bear

bison

bison

bison

bison

deer

deer

deer

eagle

eagle

eagle

eagle

falcon,

fox

fox

fox

fox

vixen

hare

hare

hare

hare /

rabbit

rabbit

rabbit

rabbit

jackal

jackal

jackal

jackal

canis aureus, hyena

leopard

leopard

leopard

leopard

cheetah

lion

lion

lion

lion

arrow

arrow battle axe

cutter

shield

lynx

lynx

owl

owl

lance, javelin, pike

aurochs stag, doe, fallow deer, antelope

raven

raven

raven

raven

crow

snake

snake

snake

snake

adder, viper, lizard

wild pig/boar

wild pig

wild boar

wild pig

hog

wolf

wolf

wolf

wolf

bitch

Appendix 3b: Lexical data This appendix gives the lexical data discussed and analyzed in chapter 6. Lexemes are organized first by language family, then by language, and thereupon by lexical concept (the two latter in alphabetical order). The next level is etymological lemmata, which are organized by their Top node, which has a label (representing the legend text of lexical maps) and a unique ID, which represent the stub of the etymological trees of the database. Thereupon follow the etymologically connected words in languages (by alphabetical order; note that the tree structure of derivations of the database is not visible). Lexemes are organized as follows (fields are distinguished by semicolon): The language name; the transcribed form of the lexeme of the database; the grammar data (adjective, verb, etc, for abbreviations see Abbreviations); the full set of meanings; the semantic coding for filtering (1 = inherited, core meaning, 2 = loan, core meaning, 3 = inherited, extended/ secondary/ colexified meaning, 4 = loan, extended/ secondary/ colexified meaning, 0 = changed meaning or proto-language form); information if the word is a loanword (Loan); source language for loans; the unique lexeme ID of the database DiACL. Ukranian and Belorussian forms, which are in the maps, are not included here. In the lemma, we give several variants of reconstructed forms; our preferred reconstruction is in the lemma header. In Caucasian families, most etymologies are connected at the root. The lemma header gives the Proto-Kartvelian reconstruction followed by etc. (Family; Word List Item [a–z]; Top Node Explanation [legend order] (Top Node Lexeme ID); Language Name [a–z]; Word Transcription; Grammatical Data; Word Meaning; ArcMap Prio; Reliability; Source Language; (Lexeme ID).)

Indo-European apple PIE *h₂eb-ōl- ‘apple’ (75287) Breton; aval; m; apple; 1; –; –; (75386). Bulgarian; jábălka; f; apple, apple-tree; 1; –; –; (75459). Bulgarian; jáblo; n; apple; 1; –; –; (75451). Bulgarian; jábol; m; apple; 1; –; –; (75455). Cornish; aval; m; apple; 1; –; –; (75398). Croatian; jȁbuka; f; apple, apple-tree; 1; –; –; (75441). Czech; jablko; n; apple; 1; –; –; (75409). Czech; jablo; n; apple; 1; –; –; (75405). Danish; æble; n; apple; 1; –; –; (75341). Dutch; appel; c; apple; 1; –; –; (75297). Elfdalian; eppel; n; apple; 1; –; –; (75366). English; apple; –; the round firm fleshy fruit of the Rosaceous tree Pyrus malus; 1; –; –; (75307). Faroese; epli, epl; n; potato; apple; 3; –; –; (75361). Gaulish; avallo; –; apple; 1; –; –; (75401). German; Apfel; m; apple; 1; –; –; (75288). Icelandic; epli; n; apple; 1; –; –; (75356). Irish; úll; m; apple; 1; –; –; (75372). Latvian; âbuõls, âbuls, âbuolis; m; apple; clover; 1; –; –; (75469). Lithuanian; obuolỹs; m; apple; 1; –; –; (75472). Middle Breton; aval; –; apple; 1; –; –; (75387). Middle Dutch; appel; m; apple; 1; –; –; (75298). Middle English; appel; –; apple; 1; –; –; (75308). Middle High German; apfel; m; apple; 1; –; –; (75289). Middle Low German; appel; m; apple; 1; –; –; (75294). Norwegian (Bokmål); eple; n; apple; 1; –; –; (75346). Norwegian (Nynorsk); eple; n; apple; 1; –; –; (75351). https://doi.org/10.1515/9783110367416-015

Old Breton; abal; –; apple; 1; –; –; (75388). Old Church Slavonic; ablъko; n; apple; 1; –; –; (75464). Old English; æpl, appel; m; apple; 1; –; –; (75309). Old Frisian; appel; m; apple; 1; –; –; (75319). Old High German; apful, apfel; m; apple; 1; –; –; (75290). Old Irish; ubull, uball; n,m; apple; 1; –; –; (75373). Old Norse; epli; n; apple; 1; –; –; (75326). Old Polish; jabɫo; n; apple; 1; –; –; (75414). Old Prussian; wabelcke; –; apple; 1; –; –; (75482). Old Prussian; wobalne; f; apple tree; 0; –; –; (75478). Old Prussian; wobilis; –; clover; 0; –; –; (75483). Old Prussian; woble; f; apple; 1; –; –; (75475). Old Saxon; appul; m; apple; 1; –; –; (75304). Old Swedish; æple; n; apple; 1; –; –; (75330). Polish; jabɫko; n; apple; 1; –; –; (75418). Proto-Balto-Slavic; *aʔb-ō-l-s, *aʔb-l-o; –; –; 0; –; –; (75407). Proto-Celtic; *abalo-; –; apple; 0; –; –; (75374). Proto-Germanic; *apla-; m; apple; 0; –; –; (75295). Proto-Indo-European; *h₂éb-ol-; –; –; 0; –; –; (75329). Proto-Indo-European; *h₂eb-ōl-, *h₂eb-l-; –; –; 0; –; –; (75408). Proto-Indo-European; *h₂eph₃ol-; –; apple; 0; –; –; (75375). Proto-North-Germanic; *apalja-, *aplja-; –; apple; 0; –; –; (75327). Proto-Slavic; *àblo, *àblъ; n,m; apple; 0; –; –; (75406). Proto-Slavic; *àblъko, *àblъka, *àblъkъ; n,f,m; apple; 0; –; –; (75410). Russian; jábloko; n; apple; 1; –; –; (75423).

434

Appendix 3b: Lexical data: Indo-European

Scottish Gaelic; ubhal; m; apple; 1; –; –; (75376). Serbian; jȁbuka; f; apple, apple-tree; 1; –; –; (75446). Slovene; jábəɫ; m; apple-tree; 0; –; –; (75432). Slovene; jáblọ; n; apple, apple-tree; 1; –; –; (75428). Slovene; jáboɫka; f; apple, apple-tree; 1; –; –; (75436). Swedish; äpple; n; apple; 1; –; –; (75335). Welsh; afal; m; apple; 1; –; –; (75383). Gr μῆλον ‘apple; fruit’ (substr.) (75486) Albanian (Tosk); mollë; f; apple, apple tree; 2; Loan; Latin; (75518). Classical Greek; μηλέη; f; apple-tree; 0; –; –; (75494). Classical Greek; μῆλον; n; apple; also of other stonefruits; (seed-)capsule of a rose, metaph. plur. breasts, cheeks, tonsils, apple-like beaker; 1; –; –; (88498). Italian; mela; f; apple (fruit); 1; –; –; (75487). Italian; melo; m; apple tree; 0; –; –; (75491). Late Latin; mela; f; apple; fruit; 1; –; –; (75488). Latin; malum; n; apple; 2; Loan; Classical Greek; (75489). Latin; mālum; n; apple; fruit; 2; Loan; Classical Greek; (75509). Latin; malus; f; apple tree; 0; Loan; Classical Greek; (75511). Latin; mālus; m; apple; 2; Loan; Classical Greek; (75493). Modern Greek; μῆλο; n; apple; 1; –; –; (75514). Romanian; măr; n,m; apple; apple tree; 1; –; –; (75500). Sardinian; mela; f; apple; 1; –; –; (75496). Vulgar Latin; melus; m; apple; fruit; 1; –; –; (75492). < PIE *h₁emo-, *h₁omo- ‘what is (to be) taken’ (75521) Catalan; pom; m; fruit; 3; –; –; (75576). Catalan; poma; f; apple; 1; –; –; (75572). English; pome; –; type of fruit; 3; –; –; (75522). French; pomme; f; apple; 1; –; –; (75524). Italian; pomo; m; fruit; knob; 3; –; –; (75535). Latin; pōmus, pōmum; m,n; fruit-tree; fruit; 0; –; –; (75526). Middle English; pome; –; apple; a fruit resembling an apple, such as pear, quince, haw; 2; Loan; French; (75523). Middle French; pon, pom; m; apple; 1; –; –; (75549). Occitan; pom; m; apple; 1; –; –; (75543). Occitan; poma; f; apple; 1; –; –; (75539). Old French; pon, pom; m; apple; 1; –; –; (75525). Old Italian; poma; f; fruit; 3; –; –; (75584). Old Italian; pómo; m; fruit tree; 0; –; –; (75588). Portuguese; pomar; m; orchard; 0; –; –; (75558). Portuguese; pomo; m; apple; fruit; 1; –; –; (75559). Proto-Indo-European; *h₁e/om-o-; v; what is (to be) taken; 0; –; –; (75528).

Proto-Italic; *po-e/omo-; –; taken off, picked; 0; –; –; (75527). Provençal; pom; m; apple; 1; –; –; (75580). Romanian; poamă; f; fruit; 3; –; –; (75563). Romanian; pom; m; fruit tree; 0; –; –; (75567). Spanish; poma; f; fruit; apple; 3; –; –; (75554). Lat (mala) mattiāna ‘juicy apple’ (75600) Latin; (mala) mattiāna; juicy apple; f; 3; –; –; (75603). Portuguese; maçã; f; apple; 1; –; –; (75604). Spanish; manzana; f; apple; 1; –; –; (75602). Spanish; manzano; m; apple tree; 0; –; –; (75601). ClArm xncor ‘apple’ (uct. etym.) (75606) Classical Armenian; xncor; –; apple; 2; Loan; Hurrian/Urartian; (75608). Modern Armenian; xnjor; –; apple; 1; –; –; (75607). PKv *mchxal- ‘pear’, etc. (93271) Classical Armenian; xncor; –; apple; 0; –; –; (75608). Classical Armenian; xncor; –; apple; 0; Loan; Proto-Nakh; (75608). Modern Armenian; xnjor; –; apple; 0; –; –; (75607). No etym. (–) Middle Persian; sēb; –; apple; 1; –; –; (94009). arrow PIE *ark-uh₂- ‘bow, arrow’ (87899) Classical Greek; ἄρκευθος; f; juniper; 0; –; –; (87961). Croatian; ràkita; f; brittle willow; 0; –; –; (87966). Czech; rokyta; f; brittle willow; 0; –; –; (87962). English; arrow; –; sharp pointed stick shot from a bow; 1; –; –; (87941). Faroese; ørv; f; arrow; 1; –; –; (87937). Gothic; arƕazna; f; arrow; 1; –; –; (87957). Latin; arcus; m; bow; arch; 0; –; –; (87901). Latvian; ẽrcis; –; juniper; 0; –; –; (87970). Middle English; aewe, arewe, arowe; –; arrow; 1; –; –; (87942). Middle English; arc; –; part of a circle or curve; arch; 0; Loan; Old French; (87950). Old English; earh; f; arrow; 1; –; –; (87943). Old French; arc; m; bow, curve, arch; 0; –; –; (87951). Old Norse; ǫr; f; arrow; 1; –; –; (87930). Old Swedish; arf; f; arrow; 1; –; –; (87933). Proto-Germanic; *arhwō-; f; arrow; 0; –; –; (87931). Proto-Germanic; *arχwō-az-; –; –; 0; –; –; (87958). Proto-Italic; *arkuo-, *arkʷo-; –; bow; 0; –; –; (87902). Proto-Slavic; *orkỳta; f; brittle willow; 0; –; –; (87963). Russian; rakíta; –; brittle willow; 0; –; –; (87964). Serbian; ràkita; f; brittle willow, osier; 0; –; –; (87968).

Appendix 3b: Lexical data: Indo-European

Lat sagitta ‘arrow’ (← Etr?) (87971) Albanian (Tosk); shigjetë, shëgjetë; f; arrow; 2; Loan; Latin; (88011). Breton; saezh; f; arrow; 1; –; –; (87982). Catalan; sageta; f; arrow; 1; –; –; (88006). Cornish; seth; f; arrow; 2; Loan; Latin; (87987). Irish; saighead; f; arrow; 1; –; –; (87972). Italian; saetta; f; thunderbolt; arrow (obsolete?); 0; –; –; (87989). Latin; sagitta; f; arrow; 1; –; –; (87974). Middle Breton; saez; –; arrow; 2; Loan; Latin; (87983). Middle French; saiete, sayette; f; arrow; 1; –; –; (87995). Occitan; sageta; f; arrow; 1; –; –; (87993). Old French; saete, saiete; f; arrow; 1; –; –; (87996). Old Irish; saiget; f; arrow; 2; Loan; Latin; (87973). Portuguese; seta; f; arrow; 1; –; –; (88002). Provençal; sageto; f; arrow; 1; –; –; (88008). Romanian; săgeată; f; arrow; 1; –; –; (88004). Sardinian; saetta; f; umbilical cord; 0; –; –; (87991). Scottish Gaelic; saighead; f; arrow; 1; –; –; (87975). Spanish; saeta; f; arrow; 1; –; –; (88000). Welsh; saeth; f; arrow; 2; Loan; Latin; (87980). Elf kuov (uct. etym.) (88013) Elfdalian; kuov; m; arrow; 1; –; –; (88014). Lat pīlum ‘javelin, spear’ (uct. etym.) (88015) Danish; pil; c; arrow; 2; Loan; Middle Low German; (88023). Dutch; pijl; c; arrow; 1; –; –; (88056). Elfdalian; pil; m; arrow; 1; –; –; (88038). Faroese; pīla; f; arrow; 1; –; –; (88035). French; pile; f; pillar; stack, pile; 0; –; –; (88067). German; Pfeil; m; arrow; 1; –; –; (88041). Icelandic; pīla; f; arrow; 1; –; –; (88032). Italian; pilo; m; lance; 0; –; –; (88065). Latin; pīlum; n; javelin, spear; 0; –; –; (88017). Middle Dutch; pijl, piel, pile; m; arrow; 2; Loan; Latin; (88057). Middle French; pile; f; javelin; 0; –; –; (88068). Middle High German; phīl; m; arrow; 1; –; –; (88042). Middle High German; phîle-strâle; m; arrow; 1; –; –; (88048). Middle Low German; pīl; m; arrow, arrowhead; 2; Loan; Latin; (88024). Norwegian (Bokmål); pil; m,f; arrow; 1; –; –; (88026). Norwegian (Nynorsk); pil; m,f; arrow; 1; –; –; (88029). Old English; pīl; m; arrow; head of an arrow or spear; 2; Loan; Latin; (88063). Old High German; pfīl; m; javelin, arrow; 0; Loan; Latin; (88043). Old Norse; píll, píla; m,f; arrow; 2; Loan; Latin; (88016). Old Saxon; pīl; m; arrow, javelin; 2; Loan; Latin; (88061).

435

Old Swedish; pil, pīla; f; arrow; 2; Loan; Latin; (88018). Romanian; pil; n; stick, rod; horsewhip; 0; –; –; (88072). Swedish; pil; c; arrow; 1; –; –; (88020). PIE *gʷelh₁o- < *gʷelh₁- ‘to hit by throwing’ (88075) Classical Greek; βάλλω; v; to throw, hit; 0; –; –; (88078). Classical Greek; βέλος; n; projectile, throwing weapon; arrow; 0; –; –; (88077). Modern Greek; βέλος; n; arrow, dart, shaft; 1; –; –; (88076). Proto-Indo-European; *gʷelh₁-; v; to hit by throwing; 0; –; –; (88079). PGm *strēlō- ‘ray, beam, stick, arrow’ < *streh₁loh₂- (88083) Bulgarian; strelá; f; arrow; 2; Loan; Germanic (branch); (88144). Croatian; strijéla; f; arrow; 2; Loan; Germanic (branch); (88140). Czech; střela; f; projectile; 0; Loan; ProtoGermanic; (88132). Dutch; straal; c; beam; water jet; 0; –; –; (88115). German; Strahl; m; ray; 0; –; –; (88100). Latvian; strēle; f; projectile, arrow; ray, beam; 0; Loan; Proto-Germanic; (88148). Lithuanian; strėlà; f; arrow (esp. in metaphorical senses); branch; 2; Loan; Germanic (branch); (88150). Middle Dutch; strael, strale; m,f,n; arrow, ray; 1; –; –; (88116). Middle English; strale; –; arrow; the pupil of the eye; 1; –; –; (88125). Middle High German; strāl, strāle; m,f; arrow; ray, beam; lightning; 1; –; –; (88101). Middle Low German; strale; f,m; arrow; beam, ray; 1; –; –; (88089). Norwegian (Bokmål); stråle; f,m; long stick, slender tree; ray, beam; jet of liquid; 0; –; –; (88084). Norwegian (Bokmål); stråle; f,m; long stick, slender tree; ray, beam; jet of liquid; 0; Loan; Middle Low German; (88084). Norwegian (Nynorsk); stråle; f,m; long stick, slender tree; ray, beam; jet of liquid; 0; –; –; (88092). Norwegian (Nynorsk); stråle; f,m; long stick, slender tree; ray, beam; jet of liquid; 0; Loan; Middle Low German; (88092). Old Church Slavonic; strěla; f; arrow; 2; Loan; Germanic (branch); (88146). Old English; strǣl; m,f; ray, beam, stick, arrow; 0; –; –; (88126). Old High German; strāl, strāla; m,f; arrow; ray, beam; 1; –; –; (88102). Old Saxon; strāla; f; arrow, beam; 1; –; –; (88122). Polish; strzała; f; arrow; 2; Loan; Germanic (branch); (88134).

436

Appendix 3b: Lexical data: Indo-European

Proto-Germanic; *strēlō-; f; ray, beam, stick, arrow; 0; –; –; (88086). Proto-Germanic; *strēlōn-; –; ray, beam, stick, arrow; 0; –; –; (88085). Russian; strelá; f; arrow; shaft; 2; Loan; Germanic (branch); (88136). Serbian; stréla; f; arrow; 2; Loan; Germanic (branch); (88142). Slovene; stréla; f; bolt of lightning; 0; Loan; Proto-Germanic; (88138). PIE *nedo- ‘reed’ (88152) Hittite; nāta-; c; reed, arrow, drinking straw; 0; –; –; (88164). Modern Armenian; net; –; arrow; 1; –; –; (88153). Persian; na/ɑy; –; reed, cane; flute, pipe; 0; –; –; (88158). Proto-Indo-European; *nedo-; –; reed; 0; –; –; (88154). Sanskrit; naḍá-; m; reed; 0; –; –; (88160). ́ f; pipe, flute, vein; 0; –; –; Sanskrit; nāḍī-; (88162). PIE *pléuk-e- < PIE *pléuk- ‘to fly’ (88166) Catalan; fletxa; f; arrow; 2; Loan; Old French; (88216). Dutch; vliek, vleek; –; arrow; 1; –; –; (88176). French; flèche; f; arrow; 1; –; –; (88191). Italian; freccia; f; arrow; 2; Loan; Old French; (88186). Latin; fleccia; f; arrow; 1; –; –; (88221). Middle Dutch; vlieke, vleke; f; feather; arrow; 0; –; –; (88177). Middle French; fleche; f; arrow; 1; –; –; (88192). Middle High German; vlücke; adj; fledged, able to fly; 0; –; –; (88167). Middle Low German; fliecke, fleke; f; long arrow; 1; –; –; (88173). Old Franconian; *fliukka; –; arrow, feather (?); 3; –; –; (88188). Old French; fleche; f; arrow; shaft of an arrow; 2; Loan; Old Franconian; (88187). Old High German; flucki; adj; fledged, able to fly; 0; –; –; (88168). Old High German; flukhi; –; arrow, projectile; 1; –; –; (88169). Old Saxon; fliuca; –; long arrow; 1; –; –; (88183). Portuguese; flecha; f; arrow; 2; Loan; Old French; (88211). Proto-Germanic; *fleugan-; v; to fly; 0; –; –; (88170). Proto-Germanic; *fleugan-; v; to fly; 0; –; –; (88189). Spanish; flecha; f; arrow; 2; Loan; Old French; (88206). PGm *bulta(n)- ‘to hit, to bump’ < PIE *bheld- ‘to knock’ (88222) English; bolt; –; arrow fired from cross-bows; discharge of lightning; pin for fastening, stout metal pin, typically fixed with a nut; 1; –; –; (88241). German; Bolz, Bolzen; m; cross-bow bolt; 3; –; –; (88223).

Latvian; bulta; f; arrow; 2; Loan; Middle Low German; (88253). Middle Dutch; bout; c; peg; 0; –; –; (88238). Middle English; bolt; –; arrow, esp. the shorter and stouter kind fired from cross-bows; discharge of lightning; 1; –; –; (88242). Middle High German; bolz; m; arrow; 1; –; –; (88224). Middle Low German; bolte, bolten; m; bolt, arrow; 0; –; –; (88235). Old English; bolt; m; bolt, arrow; 0; –; –; (88243). Old High German; bolz; m; bullet, bolt, peg; 0; –; –; (88225). Proto-Germanic; *bulta(n)-; v; to hit, to bump; 0; –; –; (88226). Proto-Indo-European; *bhld-; –; –; 0; –; –; (88227). PIE *(H)isu- ‘arrow’ (88257) Avestan; išav-; m; arrow; 1; –; –; (88260). ̓ Classical Greek; ῑός; m; arrow; 3; –; –; (88258). Proto-Indo-European; *(H)isu-; –; arrow; 0; –; –; (88259). Sanskrit; íṣu-; f,m; arrow; 1; –; –; (88262). < PIE *per- ‘to cross, pass, pierce’ (88264) Classical Greek; πείρω; v; to perforate, pierce, pervade; 0; –; –; (88265). Proto-Indo-European; *per-; –; to traverse, cross, pass; 0; –; –; (36977). Proto-Indo-European; *peroro-; –; –; 0; –; –; (88269). Proto-Tocharian; *pärere-; –; –; 0; –; –; (88268). Tocharian A; pär; m; arrow; 1; –; –; (88267). Tocharian B; prere; m; arrow; 1; –; –; (88270). Av aštay- ‘arrow’ (uct. etym.) (88273) Avestan; aštay-; m; arrow; 1; –; –; (88274). ash PIE *h₃es-n- ‘ash tree’ (43525) Albanian (Tosk); ah; m; beech; 3; –; –; (43533). Bulgarian; jásen; ósen; –; ash tree; 1; –; –; (43638). Classical Armenian; hacʿi; –; ash tree; 1; –; –; (43534). Classical Greek; ὀξύα -η; f; beech, Fagus silvatica; spear shaft (made of beech wood), spear; 3; –; –; (43535). Czech; jasan; m; ash tree; 1; –; –; (43633). Danish; ask; c; ash tree; 1; –; –; (43706). Dutch; es; c; ash tree; 1; –; –; (43717). Elfdalian; ask; m; ash tree; 1; –; –; (43705). English; ash; –; ash tree, any tree of the genus Fraxinus; 1; –; –; (43713). Faroese; ask; f; ash tree; 1; –; –; (43704). French; orne; m; kind of ash tree; 4; Loan; Latin; (43626). German; Esche; f; ash-tree; 1; –; –; (43716). Icelandic; askur; m; ash tree; 1; –; –; (43710). Irish; fuinseog; f; ash tree; 1; –; –; (43624). Italian; orno; m; kind of ash tree, Fraxinus ornus; 3; –; –; (43627). Latin; ornus; f; kind of ash tree; 3; –; –; (43537). Latvian; uôsis; m; ash tree; 1; –; –; (43629).

Appendix 3b: Lexical data: Indo-European

Lithuanian; úosis; m; ash tree; 1; –; –; (43630). Middle Breton; ounn, onn; –; ash tree; 1; –; –; (43541). Middle Dutch; asch, esche; f; ash tree; 1; –; –; (43531). Middle English; asch; –; ash tree; 1; –; –; (43714). Middle High German; asch, asche, esche; m,f; ash tree; 1; –; –; (43715). Middle Welsh; ynn; f; ash tree; 1; –; –; (43540). Norwegian (Bokmål); ask; m; ash tree; 1; –; –; (43707). Norwegian (Nynorsk); ask; m; ash tree; 1; –; –; (43708). Norwegian (Nynorsk); ask; m; ash tree; 1; –; –; (43709). Old Cornish; onnen; –; ash tree; 1; –; –; (43542). Old English; æsc; m; ash tree; spear (poetic); 1; –; –; (43532). Old High German; asc; m; ash tree; 1; –; –; (43530). Old Irish; uinnius; f; ash tree; 1; –; –; (43539). Old Norse; askr; m; ash tree; 1; –; –; (43528). Old Prussian; woasis; m; ash tree; 1; –; –; (43631). Old Swedish; asker; m; ash tree; 1; –; –; (43711). Polish; jesion; m; ash tree; 1; –; –; (43634). Proto-Balto-Slavic; *oʔs-en-, *oʔs-i-o-; –; ash; 0; –; –; (43543). Proto-Celtic; *osno-; –; ash tree; 0; –; –; (43526). Proto-Germanic; *aska-; m; ash tree; 0; –; –; (43527). Proto-Indo-European; *h₃es-n-; –; ash tree; 0; –; –; (43525). Proto-Italic; *osVno-; –; ash; 0; –; –; (43536). Proto-Slavic; *àsenь, àsenъ; m; ash tree; 0; –; –; (43549). Romanian; urm; m; kind of ash tree, Fraxinus ornus; 3; –; –; (43628). Russian; jásen’; m; ash tree; 1; –; –; (43632). Scottish Gaelic; uinnseann; –; ash tree; 1; –; –; (43625). Serbo-Croatian; jȁsēn; m; ash tree; 1; –; –; (43635). Slovene; jásen; m; ash tree; 1; –; –; (43636). Swedish; ask; c; ash tree; 1; –; –; (43712). Welsh; onnen; f; ash tree; 1; –; –; (43703). PIE *bhrHǵ- ‘birch tree’ (53958) Catalan; freixe; m; ash tree; 1; –; –; (43701). French; frêne; m; ash tree; 1; –; –; (43675). Italian; frassino; m; ash tree; 1; –; –; (43698). Latin; fraxinus; f; ash tree; 1; –; –; (43674). Occitan; fraisse; m; ash tree; 1; –; –; (43702). Old French; fresne; m; ash tree; 1; –; –; (43676). Portuguese; freixo; m; ash tree; 1; –; –; (43700). Proto-Italic; *frakse/ino-; –; –; 0; –; –; (43673). Spanish; fresno; m; ash tree; 1; –; –; (43699). No etym. (–) Classical Greek; μελία; f; ash tree; lance made of ash-wood; 1; –; –; (43575).

437

autumn < PGm *waiþō- ‘to graze, to hunt’ (55909) Old Franconian; *waidanjan; –; autumn; 1; –; –; (55969). Old French; gain; m; harvest time; acquisition; 4; Loan; Old Franconian; (83323). Proto-Germanic; *waiþō-; –; –; 0; –; –; (55911). < PIE *krp- ‘to pick, pluck’ (76949) Danish; høst; c; the harvest (reaping and gathering in); harvest-time; the harvested crop; (rare, poetic) autumn; 3; –; –; (83172). Dutch; herfst; c; autumn; 1; –; –; (83234). Elfdalian; ost; m; autumn; 1; –; –; (83202). English; harvest; –; the work of reaping and gathering in of ripened grain, the produce of this work; the season for harvesting; 3; –; –; (83247). Faroese; heyst; n; autumn; 1; –; –; (83196). Frisian; harvst, hearst, herst; m; autumn; 1; –; –; (83262). German; Herbst; m; autumn; 1; –; –; (83208). Icelandic; haust; n; autumn; 1; –; –; (83190). Latin; carpere; v; to pluck, gather; 0; –; –; (76959). Latvian; cìrpt; v; to shave; 0; –; –; (83274). Low German; harvst, harfst; m; autumn; 1; –; –; (83223). Middle Dutch; herfst, heerfst, herft; m; harvest, autumn; 3; –; –; (83235). Middle English; hærfest, herfest, hervest; –; autumn; harvest season; (later): the harvest (reaping and gathering in); the ripened crop; 1; –; –; (83248). Middle High German; herbest; m; autumn; 1; –; –; (83214). Middle Low German; herbest; m; autumn; 1; –; –; (83209). Middle Low German; hervest, hervst; m; autumn; 1; –; –; (83224). Norwegian (Bokmål); høst; m; autumn; 1; –; –; (83178). Norwegian (Nynorsk); haust; m; autumn; harvested crop; 1; –; –; (83184). Old English; hærfest, hęrfest; m; harvest; autumn; harvest season; 3; –; –; (76952). Old Frisian; herfst; m; autumn; 1; –; –; (83263). Old High German; herbist; m; harvest; autumn; 3; –; –; (76950). Old Norse; haust; n; autumn; 1; –; –; (83154). Old Norse; haustr; m; autumn; 1; –; –; (83155). Old Saxon; hẹrvist; m; autumn (?); 1; –; –; (83225). Old Swedish; höster; m; autumn; 1; –; –; (83159). Proto-Germanic; *harbista-; m; autumn; 0; –; –; (83156). Proto-Germanic; *harbjan-; v; to pluck; 0; –; –; (83157). Proto-Indo-European; *kerp-e/o-; v; to pick, pluck; 0; –; –; (83273). Proto-Indo-European; *krp-; v; to pick, pluck; 0; –; –; (83158).

438

Appendix 3b: Lexical data: Indo-European

Proto-Italic; *karp-; –; –; 0; –; –; (83272). Swedish; höst; c; autumn; 1; –; –; (83165). PIE *ǵh(e)i-m- ‘winter’ (81897) Czech; podzim; m; autumn; 1; –; –; (83369). Proto-Balto-Slavic; *źeimaʔ; –; –; 0; –; –; (82124). Proto-Indo-European; *ǵhei-m-eh₂-; –; –; 0; –; –; (82125). Proto-Slavic; *zimà; f; winter; 0; –; –; (82123). PIE *ieh₁-ro- ‘year, summer’ (83276) Danish; år; n; year; 3; –; –; (82387). Danish; efterår; n; autumn; 1; –; –; (83277). Dutch; najaar; n; autumn; 1; –; –; (83293). German; Jahr; n; year; 3; –; –; (60612). German; Spätjahr; n; (late) autumn; 1; –; –; (83282). Middle Dutch; jaar; n; year; 3; –; –; (83295). Middle Dutch; najaer; n; year of grace; 3; –; –; (83294). Middle English; fore-year; –; early part of the year; 0; –; –; (83302). Middle High German; jār; n; year; 3; –; –; (60613). Middle High German; nâchjâr; n; autumn; next year; 1; –; –; (83288). Old High German; jār; n; year; 3; –; –; (60614). Old Norse; ár; n; year; 3; –; –; (82388). Proto-Germanic; *jēra-; n; year; 0; –; –; (60615). Proto-Indo-European; *ieh₁-ro-; –; year, summer; 0; –; –; (60616). Lat autumnus ‘autumn’ (← Etr?) (83305) Catalan; autumne; m; autumn (poetic); 1; –; –; (83319). French; automne; m; autumn; 1; –; –; (83308). Italian; autunno; m; autumn; 2; Loan; Latin; (83306). Latin; autumnus; m; autumn; 1; –; –; (83307). Old French; automne, auptonne; f; autumn; 2; Loan; Latin; (83309). Portuguese; outono; m; autumn; 1; –; –; (83315). Romanian; toamnă; f; autumn; 1; –; –; (83317). Spanish; otoño; m; autumn; 1; –; –; (83313). Lat tardatiōne ‘arriving late’ (83326) Catalan; tarda; f; afternoon; 0; –; –; (83328). Catalan; tardor; f; autumn; 1; –; –; (83327). Latin; tardatiōne; adv; arriving late; 0; –; –; (83329). Alb vjeshtë ‘autumn’ < PIE *wel- ‘to shut in, to press’ (83363) Albanian (Tosk); vjel; v; to pluck fruit, to vintage; 0; –; –; (83365). Albanian (Tosk); vjeshtë; f; autumn; 1; –; –; (83364). Lithuanian; su-valýti; v; to harvest, to reap; 0; –; –; (83367). Proto-Albanian; *wela; –; –; 0; –; –; (83366). PIE *h₁roudh-o- ‘red; reddish-brown’ (83373) Latvian; rudens; m; autumn; 1; –; –; (83374). Latvian; ruds; adj; reddish-brown; 0; –; –; (83375). Lithuanian; rùdas; adj; reddish-brown; 0; –; –; (83379).

Lithuanian; ruduõ; m; autumn; 1; –; –; (83378). Proto-Balto-Slavic; *roudos; –; –; 0; –; –; (83376). Proto-Indo-European; *h₁roudh-o-; –; –; 0; –; –; (83377). Wel hydref, Br hezreff ‘autumn’ (uct. etym.) (83382) Breton; here; m; October (formerly autumn); 3; –; –; (83384). Cornish; hedra; m; october; 3; –; –; (83388). Middle Breton; hezr; adj; powerful; courageous, tough; 0; –; –; (83386). Middle Breton; hezreff; –; october; 3; –; –; (83385). Welsh; hydref; m; autumn; October; 1; –; –; (83383). Br diskar-amzer ‘autumn’ (83389) Breton; diskar-amzer; f; autumn (lit. fall-season, fall-time); 1; –; –; (83390). IIr *ćarad- ‘year; autumn’ (uct. etym.) (83391) Avestan; sarəd-; f; year; 3; –; –; (83395). Lithuanian; šìlius; m; August; 3; –; –; (83393). Lithuanian; šìlti; v; grow warm; 0; –; –; (83392). Old Persian; θard-; f; –; year; 3; –; –; (83396). Ossetian (Iron); særd; –; summer; 3; –; –; (83394). Persian; sɑl; –; year; 3; –; –; (83397). Sanskrit; śarad-; f; year; autumn; 3; –; –; (83398). Hitt zēna- ‘autumn’ < PIE *tiéh₁-no- (uct. etym.) (83399) Hittite; zēna-; –; autumn; 1; –; –; (83400). Proto-Indo-European; *tiéh₁-no-; –; –; 0; –; –; (83401). PIE *h₁os-r/n- ‘harvest-time’ (88502) Bulgarian; ésen; f; autumn; 1; –; –; (83350). Classical Greek; φθινόπωρον; n; late autumn, fall of the year; 1; –; –; (83360). Croatian; jȅsēn; f; autumn; 1; –; –; (83344). Czech; jeseň; f; autumn; 1; –; –; (83332). Modern Armenian; ašun-, ašnan-; –; autumn; 1; –; –; (83331). Modern Greek; φθινόπωρο; n; autumn; 1; –; –; (83359). Old Church Slavonic; esenь; f; autumn; 1; –; –; (83353). Old Prussian; assanis; f; autumn; 1; –; –; (83356). Polish; jesień; f; autumn; 1; –; –; (83335). Proto-Balto-Slavic; *es-eni-; –; –; 0; –; –; (83334). Proto-Indo-European; *h₁e/os-oni-; –; –; 0; –; –; (83357). Proto-Indo-European; *h₁os-r/n-; –; harvest-time, summer; 0; –; –; (83362). Proto-Slavic; *ȅsenь; f; autumn; 0; –; –; (83333). Russian; ósen’; f; autumn; 1; –; –; (83338). Serbian; jȅsēn; f; autumn; 1; –; –; (83347). Slovene; jesę̑n; f; autumn; 1; –; –; (83341). axe < PIE *teḱs- ‘to hew, to fabricate’ (71546) Avestan; taša-; m; adze; 1; –; –; (78895). Bulgarian; teslá; f; adze; 1; –; –; (78885). Croatian; tȅsla; f; adze; 1; –; –; (78879).

Appendix 3b: Lexical data: Indo-European

Czech; tesla; f; adze; 1; –; –; (78861). Danish; tengsel; c,n; adze; 1; –; –; (78803). Dutch; dissel; c; adze; 1; –; –; (78836). German; Dechsel; f; adze; 1; –; –; (78798). Icelandic; þexla; f; adze; 1; –; –; (78817). Irish; tál; m; cooperʼs adze or axe; 1; –; –; (78847). Irish; tál fuinn; m; hoe; 3; –; –; (78846). Lithuanian; tasz-ýti; v; to hew or shape with the axe; 0; –; –; (78894). Middle Dutch; dissel, dissele; m; adze; 1; –; –; (78837). Middle English; þixil, þixel; –; adze; 1; –; –; (78843). Middle High German; dëhse, dëhsel; f; adxe; 1; –; –; (78822). Middle Low German; desele, dessel, deissel; f; adze; 1; –; –; (78833). Norwegian (Nynorsk); diksel; f; hammer with axe blade on one side; 4; Loan; German; (78811). Norwegian (Nynorsk); teksle; f; small axe; 1; –; –; (78807). Old Church Slavonic; tesati; v; to hew; 0; –; –; (78888). Old Church Slavonic; tesla; f; adze; 1; –; –; (78890). Old High German; dehsa, dehsala; f; adze; 1; –; –; (78800). Old Irish; tál; m; adze; 1; –; –; (78848). Old Norse; þexla; f; adze; 1; –; –; (78790). Persian; tæš; –; axe; 1; –; –; (78896). Polish; ciosɫa; f; adze; 1; –; –; (78864). Proto-Celtic; *tāxslo-; –; axe; 0; –; –; (78849). Proto-Germanic; *tōkslo-; –; –; 0; –; –; (78791). Proto-Indo-European; *teḱ-s-; v; to hew, fabricate; to fashion; 0; –; –; (71548). Proto-Indo-European; *teḱs-slo-; –; axe; 0; –; –; (78850). Proto-Indo-European; *tetḱ-; –; –; 0; –; –; (78889). Proto-Indo-European; *tetḱ-dhlo-; –; –; 0; –; –; (78860). Proto-Slavic; *tesla; f; adze; 0; –; –; (78859). Proto-Slavic; *teslò; n; adze; 0; –; –; (78871). Romanian; teslă; f; adze; 2; Loan; Slavic (branch); (78858). Russian; teslá; f; adze; 1; –; –; (78867). Russian; tesló; n; adze; 1; –; –; (78870). Scottish Gaelic; tàl; m; adze; 1; –; –; (78851). Serbian; tȅsla; f; adze; 1; –; –; (78882). Slovene; tésla; f; adze; 1; –; –; (78873). Slovene; téslọ; n; adze; 1; –; –; (78876). Swedish; däxel; c; adze; 2; Loan; German; (78797). Swedish; täxla; c; adze; 3; –; –; (78793). PIE *sok-éh₂- ‘cutting implement’ < PIE *sekh₁ie/o- ‘to cut off’ (76721) Croatian; sjèkira; f; axe; 2; Loan; Latin; (79029). French; scier; v; to cut; 0; –; –; (78405). Friulian; sêe; v; to cut; 0; –; –; (78434). Italian; scure; f; axe; 1; –; –; (78944).

439

Italian; segare; v; to cut with a saw; 0; –; –; (78387). Latin; secāre; v; to cut, sever; 0; –; –; (78384). Latin; sēcula; f; sickle, scythe; 3; –; –; (78442). Latin; secūris; f; axe; 1; –; –; (78449). Modern Greek; τσεκούρι; n; axe; 2; Loan; Latin; (79014). Occitan; segar; v; to reap, to harvest; 0; –; –; (78396). Old Church Slavonic; sěkyra; f; axe; 2; Loan; Latin; (79039). Polish; siekiera; f; axe; 2; Loan; Latin; (79019). Portuguese; segadeira; f; scythe; 3; –; –; (78417). Portuguese; segado; ppart; cut; 0; –; –; (78980). Portuguese; segar; v; to cut (grass, cereals. etc); 0; –; –; (78418). Portuguese; segure; –; axe; 1; –; –; (78974). Proto-Indo-European; *sekh₁-ie/o-; v; to cut off; 0; –; –; (76793). Proto-Italic; *sekaje/o-; –; –; 0; –; –; (78385). Provençal; segar; v; to cut; 0; –; –; (78430). Romanian; secure; f; axe; 1; –; –; (78989). Sardinian; segare; v; to cut; 0; –; –; (78391). Serbian; sèkira; f; axe; 2; Loan; Latin; (79034). Slovene; sekira; f; axe; 2; Loan; Latin; (79024). Spanish; segar; v; to cut; 0; –; –; (78413). Spanish; segur; f; axe; 3; –; –; (78965). PIE *skérH-e- ‘cutting implement’ < PIE *(s)kerH‘to cut’ (76964) Classical Greek; κεíρω; v; to cut (off), shave, shear; 0; –; –; (79045). Latvian; cirvis; m; axe; 1; –; –; (79051). Lithuanian; kir˜vis; m; axe; 1; –; –; (79054). Proto-Balto-Slavic; *kirw(i)os; –; –; 0; –; –; (79049). Proto-Indo-European; *sker-; v; to cut; 0; –; –; (79046). Proto-Slavic; *čьrvъ; m; –; 0; –; –; (79048). Russian; červ’; m; sickle; 3; –; –; (79047). Sanskrit; kr̥vi-; m; weaverʼs instrument; 3; –; –; (79057). < PIE *h₂eǵ- ‘to push’ (77711) French; aisseau, aisceau; m; hatchet, barrelmakerʼs curved hatchet; 3; –; –; (78642). French; aissette; f; barrel-makerʼs curved hatchet; rooferʼs hammer; 3; –; –; (78646). Italian; ascia; f; adze; 1; –; –; (78639). Latin; *asciāta; f; cutting implement; 3; –; –; (77713). Latin; *asciŏla; f; cutting implement; 3; –; –; (77716). Latin; ascĭa; f; spade, adze, tool for digging the earth or for cutting stone; 3; –; –; (77714). Old French; aisse; f; hatchet; 3; –; –; (78643). Portuguese; enxada; f; mattock, hoe, spade; 3; –; –; (77712). Portuguese; enxó; f; adze; 1; –; –; (77715). Spanish; azuela; f; adze; 1; –; –; (78653). PIE *peleḱus- ‘axe’ (78634) Classical Greek; πέλεκυς; m; axe, double axe, hatchet; 1; –; –; (78635).

440

Appendix 3b: Lexical data: Indo-European

Ossetian (Iron); færæt; –; axe; 1; –; –; (78636). Sanskrit; paraśú-; m; axe, battle-axe; 1; –; –; (78637). PIE *h₂egʷis-ih₂- ‘axe’ (78638) Classical Greek; ἀξίνη; f; axe; 1; –; –; (78745). Danish; økse; c; axe; 1; –; –; (78679). Dutch; aks; c; axe; 1; –; –; (78717). Elfdalian; ökse; f; axe; 1; –; –; (78699). English; axe; –; tool for hewing, cleaving or chopping trees, wood, ice, etc, consisting of a squarish iron head with sharp edge fixed upon a handle of wood; 1; –; –; (78727). Faroese; øks; f; axe; 1; –; –; (78695). German; Axt; f; axe; 1; –; –; (78702). Gothic; aqizi; f; axe; 1; –; –; (78742). Icelandic; oxi; f; axe; 1; –; –; (78691). Middle Dutch; aks, akes, akse, aex, aexe; f; axe; 1; –; –; (78718). Middle English; ax; –; axe; 1; –; –; (94217). Middle High German; ackes; f; axe; 1; –; –; (78703). Middle Low German; akes, axe, exe; f; axe; 1; –; –; (78714). Norwegian (Bokmål); øks; m,f; axe; 1; –; –; (78683). Norwegian (Nynorsk); øks; f; axe; 1; –; –; (78687). Old English; acus, æsc, æx; f; axe; 1; –; –; (94218). Old Frisian; axe; f; axe; axle; 1; –; –; (78739). Old High German; ackus; f; axe; 1; –; –; (78704). Old Norse; øx, ax; f; axe; 1; –; –; (78667). Old Saxon; akus; f; axe; 1; –; –; (78724). Old Swedish; yxa, öxe; f; axe; 1; –; –; (78670). Proto-Germanic; *akʷesī-; f; axe; 0; –; –; (78668). Proto-Indo-European; *h₂egʷs-i-; –; –; 0; –; –; (78746). Proto-Indo-European; *h₂esk-ieh₂-; –; –; 0; –; –; (78641). Swedish; yxa; c; axe; 1; –; –; (78674). Occ pigassa ‘axe’ (no etym.) (78747) Catalan; pica; f; pike; 4; Loan; Middle French; (78771). Italian; picca; m; pike; 4; Loan; Middle French; (78752). Middle Dutch; pīke, piek, pijc; m; pointed implement; 3; –; –; (78748). Middle English; pike, pick; –; spike, pickaxe, pitchfork; 4; Loan; Middle French; (78749). Middle French; pike, pique; f; a weapon, short spear; 0; Loan; Middle Dutch; (78750). Occitan; pic; m; pick, pickaxe; 4; Loan; Middle French; (78756). Occitan; pigassa; f; axe; 1; –; –; (78755). Occitan; pigasson; m; hatchet; 3; –; –; (78759). Portuguese; pica, pique; m; pike, lance; 4; Loan; Middle French; (78768). Spanish; pica; f; pike; 4; Loan; Middle French; (78765). PIE *Hodh-es-on- ‘adze, axe’ (78774) English; adze; –; a tool similar to an axe, with a blade set at right angles to the shaft; 1; –; –; (78775).

Hittite; ateš(ša)-; n; adze, axe, hatchet; 1; –; –; (78787). Middle English; adese; –; adxe; 1; –; –; (78776). Old English; adesa, eadesa, adese; m,f; adze; 1; –; –; (78777). Proto-Germanic; *adesan-; m; adze; 0; –; –; (78778). Proto-Indo-European; *Hodh-es-on-; –; –; 0; –; –; (78779). Lat *marculus ‘small hammer’ (78897) Latin; marcŭlus; m; small hammer; 3; –; –; (78901). Latin; marcus; m; hammer; 3; –; –; (78902). Portuguese; machada; f; small axe, hatchet; 1; –; –; (78898). Portuguese; machado; m; axe; 1; –; –; (78899). Vulgar Latin; *marculātus; m; little hammer; 3; –; –; (78900). < PIE *dolh₁-ye/o- ‘to cut repeatedly’ (78903) French; doloir; m; leather-workerʼs knife, used for scraping skins; 3; –; –; (78915). French; doloire; f; axe used by carpenters and barrel-makers; masonʼs shovel, used for mixing mortar; medieval battle-axe; 1; –; –; (78909). Latin; dolābra; f; a pick or similar tool; 3; –; –; (78926). Latin; dolāre; v; to hew or chop into shape; 0; –; –; (78906). Occitan; doladoira; f; axe; 1; –; –; (78904). Old French; doleoire; f; axe, carpenterʼs tool; 1; –; –; (78910). Proto-Indo-European; *dolh₁-ie/o-, *d(e)lh₁-ie/o-; v; to cut; 0; –; –; (78908). Proto-Italic; *dolaje-; –; –; 0; –; –; (78907). Vulgar Latin; dolatōria; f; axe; 1; –; –; (78905). Lat cuneus ‘wedge’ (no etym.) (78930) French; cognée; f; large, long-handled woodmanʼs axe; 3; –; –; (78931). Late Latin; cuneata, cuneata ascia; f; axe with a wedge-shaped head; 1; –; –; (78932). Latin; cuneus; m; wedge; 3; –; –; (78933). PSl *sěkavica- ‘axe’ (no etym.) (78935) Albanian (Tosk); sakavicë; f; long hook for pulling down branches; 4; Loan; Bulgarian; (78938). Albanian (Tosk); sakë; f; axe; 1; –; –; (78937). Albanian (Tosk); sakicë; f; small axe; 1; –; –; (78936). Bulgarian; sekíca; f; axe; 1; –; –; (78939). Proto-Slavic; *sěkavica; f; –; 0; –; –; (78940). PSl *toporъ ‘axe’ (← Pers tabar ‘axe’) (79059) Albanian (Tosk); topër; f; small axe; 2; Loan; Slavic (branch); (79070). Bulgarian; topór; m; axe; 1; –; –; (79082). Czech; topor; m; axe, adze; 1; –; –; (79073). Old Church Slavonic; toporъ; m; axe; 1; –; –; (79085). Old English; taperæx; f; small axe; 2; Loan; Old Norse; (79063). Old Norse; taparøx; f; small battle-axe; 2; Loan; Slavic (branch); (79060).

Appendix 3b: Lexical data: Indo-European

Persian; tabar; –; axe; 1; –; –; (79062). Polish; topór; m; axe, adze; 1; –; –; (79076). Proto-Slavic; *toporú; *toporъ;m; axe; 0; Loan; Persian; (79061). Romanian; topor; n; axe; 2; Loan; Slavic (branch); (79067). Russian; topór; m; axe; 1; –; –; (79079). PGm *barda, PSl *bordy (← PGm) (79088) Croatian; brȁdva; f; adze; 1; –; –; (79151). Dutch; baard; –; broad axe; 3; –; –; (79116). English; halberd; –; combined spear and battleaxe; 3; –; –; (79123). French; hallebarde; f; halberd; 4; Loan; Middle High German; (79146). German; Barte; f; broad axe; 3; –; –; (79096). German; Hellebarde; f; halberd; 3; –; –; (79100). Icelandic; barða; f; hammer used to stun fish; 3; –; –; (79093). Italian; alabarda; f; halberd; 4; Loan; Middle High German; (79141). Middle Dutch; barde; f; broad axe; 3; –; –; (79117). Middle English; haubert, hauberde, halberde; –; combined spear and battleaxe; 4; Loan; Old French; (79124). Middle English; sparth; –; long-handled broadbladed battle-axe, used especially by the Irish down to the 16th century; 4; Loan; Old Norse; (79136). Middle High German; barte; f; broad axe; 3; –; –; (79097). Middle High German; helm-barte; f; halberd; 3; –; –; (79101). Middle Low German; barde; f; broad axe; 3; –; –; (79114). Old Church Slavonic; brady; f; axe; 1; –; –; (79155). Old English; bard; –; axe; 1; –; –; (79139). Old French; hallebarde; f; halberd; 4; Loan; Middle High German; (79125). Old High German; barta; f; axe; 1; –; –; (79098). Old Norse; barða; f; battle-axe; 1; –; –; (79089). Old Norse; sparða; f; battle axe, broad axe; 1; –; –; (79091). Old Saxon; barda; f; axe; 1; –; –; (79121). Proto-Germanic; *barda-; –; axe, hammer; 0; –; –; (79090). Proto-Slavic; *bordy; f; –; 0; –; –; (79152). Serbian; brȁdva; f; adze; 1; –; –; (79153). < PIE *kop- ‘strike, smite, hew’ (79157) Albanian (Tosk); kep; v; to hew; 0; –; –; (79208). Classical Greek; κόπτω; v; to strike, smite, hew, hammer, disable, tire out; beat, hit; hew; 0; –; –; (79204). English; hatchet; –; small axe; 1; –; –; (79160). French; hache; f; axe; 1; –; –; (79170). French; hache d’armes; f; battle-axe; 1; –; –; (79179). French; hachette; f; small axe; 1; –; –; (79174). Latvian; kapât; v; to chop, hew; 0; –; –; (79212).

441

Lithuanian; kapóti; v; to chop, hew; 0; –; –; (79216). Lithuanian; kàpti; v; to hew, fell; 0; –; –; (79214). Middle English; hachet; –; hatchet; small axe; 4; Loan; Old French; (79161). Old French; hache; f; axe; 2; Loan; Germanic (branch); (79163). Old French; hachete; f; small axe; 1; –; –; (79162). Old High German; happa, heppa; f; sickle-shaped knife; 3; –; –; (79158). Old Italian; accia; f; axe; 2; Loan; Old Provençal; (79198). Old Provençal; acheta; f; small axe; 1; –; –; (79202). Old Provençal; apcha; f; axe; 2; Loan; Germanic (branch); (79188). Portuguese; acha; f; battle-axe; 2; Loan; Old French; (79191). Proto-Germanic; *happja; –; sickle, knife; sharp axe; 0; –; –; (79159). Proto-Indo-European; *kop-; v; to strike, smite, hew; 0; –; –; (79209). Russian; kopát’; v; to hew, dig; to dig; 0; –; –; (79210). Spanish; hacha; f; axe; 2; Loan; Old Provençal; (79187). < PIE *bheid- ‘to split, cut’ (79218) Breton; bouc’hal; f; axe; 1; –; –; (79325). Croatian; bȉti; v; to strike; 0; –; –; (79338). Czech; biti; v; to strike; 0; –; –; (79330). Danish; bild; c; stonecutterʼs tool; 3; –; –; (79245). Danish; bill; –; knife; 0; –; –; (79250). Dutch; bijl; c; axe; 1; –; –; (79289). English; bill, billhook; –; implement having a long blade with a curved end, often ending in a sharp hook, used for pruning, cutting wood, lopping trees, hedges, etc; heavy thick knife or chopper with a curved end, used for pruning, etc; 3; –; –; (79298). German; Beil; n; axe; 1; –; –; (79270). Irish; bainim; v; I cut, strip, strike, pluck, lift; 0; –; –; (79316). Irish; biail; f; axe; 1; –; –; (79313). Middle Breton; bouhazl; –; axe; 1; –; –; (79326). Middle Dutch; bijl; f,n; axe; 1; –; –; (79290). Middle English; bill; –; digging implement, mattock, pickaxe; various forms of bladed weapon; 3; –; –; (79299). Middle High German; bīl; n; axe; 1; –; –; (79271). Middle Low German; bil, bile; f; axe; 1; –; –; (79256). Norwegian (Bokmål); bile; m,f; hatchet, wood axe with short handle and broad blade; 4; Loan; Middle Low German; (79255). Norwegian (Nynorsk); bild; m; iron tool; knife for medicinal bloodletting; 0; –; –; (79260). Norwegian (Nynorsk); bile; f; broad-bladed wood axe; battleaxe (obsolete); 4; Loan; Middle Low German; (79265).

442

Appendix 3b: Lexical data: Indo-European

Old Church Slavonic; biti; v; to strike; 0; –; –; (79342). Old English; bill; –; broadsword, halberd, various forms of bladed weapon; 0; –; –; (79300). Old High German; bīhal; n; axe; 1; –; –; (79272). Old Irish; benaid; v; to cut, to strike; 0; –; –; (79317). Old Irish; bíail, biáil; m,f; axe; 1; –; –; (79314). Old Norse; bílda; f; arrow; 0; –; –; (79219). Old Norse; bíldr; m; knife (for medicinal bloodletting); tool for cutting, splitting, hacking, etc; 0; –; –; (79223). Old Swedish; bīlder; v; tool for cutting, splitting, hacking, etc; 3; –; –; (79227). Polish; bić; v; to strike; 0; –; –; (79332). Proto-Germanic; *bītan-; v; to bite, be sharp; 0; –; –; (79221). Proto-Germanic; *bīþla-; m; axe; 0; –; –; (79220). Proto-Indo-European; *bhei-; –; –; 0; –; –; (79222). Russian; bit’; v; to strike; 0; –; –; (79334). Serbian; bȉti; v; to strike; 0; –; –; (79340). Slovene; bíti; v; to strike; 0; –; –; (79336). Swedish; bill, plogbill; c; plowshare; 3; –; –; (79232). Swedish; isbill; c; ice chisel, crowbar; 3; –; –; (79238). Welsh; bwyall; f; axe; 1; –; –; (79323). < PIE *(s)tewg- ‘put in vehement motion’ (79344) Irish; tua; f; axe, hatchet; 1; –; –; (79346). Irish; tuagh chuisleann; f; lancet; 0; –; –; (79348). Irish; tuargain; v; to strike, to beat; 0; –; –; (79349). Old Irish; túag; f; axe, hatchet; 1; –; –; (79347). Old Irish; tuagaid; v; to hack, chop; 0; –; –; (79353). Old Norse; þoka; v; to move, to change; 0; –; –; (79345). Sanskrit; tuj-; v; to strike; 0; –; –; (79354). Scottish Gaelic; tuagh; f; axe, hatchet; 1; –; –; (79350). < PIE *wedh- ‘to push, hit’ (79355) Latvian; vedga; f; ice axe, crowbar; 3; –; –; (79356). Lithuanian; vedegà; f; a kind of axe; 1; –; –; (79358). Old Prussian; wedigo; –; carpenterʼs axe; 1; –; –; (79360). Proto-Indo-European; *wedh-; v; to push, to hit; 0; –; –; (79357). TB peret (← IIr) (79362) Proto-Tocharian; *peretä; –; –; 0; –; –; (79364). Tocharian B; peret; m; axe; 1; –; –; (79363). Hitt šummittant- ‘axe’ < PIE *smeit- ‘throw’ (79365) Hittite; šummittant-; c; axe; 1; –; –; (79366). PIE *ḱs-tro- ‘knife’ (86966) Albanian (Tosk); thadër; f; double-sided axe; 3; –; –; (86967). Proto-Albanian; *tsestrā; –; –; 0; –; –; (86968).

Proto-Indo-European; *ḱs-tro-; –; knife; 0; –; –; (86969). axle PIE *h₂egʷis-ih₂- ‘axe’ (78638) Old Frisian; axe; f; axe; axle; 0; –; –; (78739). Gr ἅμαξα ‘wagon’ (uct. etym.) (79971) Classical Greek; ἅμαξα; f; framework, chassis of a four-wheeled wagon; wagon; four-wheeled cart; 3; –; –; (79972). PIE *kʷel-o- ‘wheel, circle’ < PIE *kʷel(H)- ‘to turn’ (79981) Classical Greek; πέλομαι; v; to become, take place, be; 0; –; –; (80759). Classical Greek; πόλος; m; axis, world axis, pole, vault of heaven, disc of the sundial, etc; 1; –; –; (80758). Latin; pŏlus; m; pole (of the world); the north; the north star; the sky; 2; Loan; Classical Greek; (80757). Proto-Indo-European; *kʷlh₁-; v; to go round; 0; –; –; (80760). PIE *h₂eḱs-(i-) ‘axle, arm-pit’ (80380) Albanian (Tosk); ashkë; f; wood splinter; 0; –; –; (80579). Avestan; aša-; m; armpit; shoulder; 3; –; –; (80582). Breton; ahel; m; axle; axis; 1; –; –; (80559). Bulgarian; ósa; f; axle; 1; –; –; (80689). Catalan; eix; m; axis, axle; 1; –; –; (80641). Classical Greek; ἄξων, -oνoς; m; axle; axis; 1; –; –; (80572). Cornish; eghel, aghel; f; axle, axis; 1; –; –; (80564). Croatian; ȏs; f; axle; 1; –; –; (80677). Croatian; osòvina; f; axle; 1; –; –; (80673). Czech; osa; f; axis; 1; –; –; (80657). Danish; akse; c; axis; 2; Loan; German; (80451). Danish; aksel; c; axle, axis; 1; –; –; (80447). Dutch; as; c; axle; 1; –; –; (25862). Dutch; oksel; c; armpit; 3; –; –; (80400). Elfdalian; aksel; m; axle; 1; –; –; (80491). English; axle; –; centre-pin or spindle upon which a wheel revolves; 1; –; –; (80527). English; axle-tree; –; the fixed bar or beam of wood, etc, on the rounded ends of which the opposite wheels of a carriage revolve; 1; –; –; (80591). Faroese; aksil; m; axle; 1; –; –; (80487). Faroese; øksl; f; shoulder; 3; –; –; (80384). French; aisselle; f; armpit; 3; –; –; (80427). French; essieu; m; axle; 1; –; –; (80628). German; Achse; f; axle; 1; –; –; (80452). German; Achsel; f; shoulder, armpit; 3; –; –; (80388). German; Himmelachse; f; celestial axis; 1; –; –; (80501). German; Radachse; f; axle-tree; 1; –; –; (80495). Gothic; *ahsuls; f; axle; 1; –; –; (80542). Icelandic; öxull; m; axle, axis; 1; –; –; (80483). Irish; acastóir, acaistéar; m; axle; 2; Loan; Middle English; (80608).

Appendix 3b: Lexical data: Indo-European

Irish; aiseal; m; axle; 2; Loan; Middle English; (80545). Irish; ascaill; f; armpit; 4; Loan; Middle English; (80420). Italian; asse; m; axis; pole; board; 1; –; –; (80615). Italian; sala; f; axle; 1; –; –; (80619). Late Latin; axilla; f; axle, armpit; 3; –; –; (80429). Latin; axilla; f; armpit, wing; 3; –; –; (80430). Latin; axis; m; axle; chariot; axis, especially the Earthʼs axis; sky; firmament; 1; –; –; (80431). Latvian; ass; f; axle; axis; 1; –; –; (80697). Lithuanian; ašìs; m; axle; axis; 1; –; –; (80700). Middle Breton; ahel; –; axle; axis; 1; –; –; (80560). Middle Dutch; asse; f; axle; 1; –; –; (80518). Middle Dutch; ocsele, oxel, oxele; f; armpit; 3; –; –; (80401). Middle English; ax; –; axle; 0; –; –; (78728). Middle English; axeltre; –; axle; axle-tree; 2; Loan; Old Norse; (80592). Middle English; axil, axel, axell, axile; –; axle; 2; Loan; Old Norse; (80528). Middle English; axtre, axtreo; –; axle-tree; 1; –; –; (80599). Middle English; okselle; –; armpit; 4; Loan; Middle Dutch; (80410). Middle High German; ahse, ehse; f; axle, axletree; celestial axis; 1; –; –; (80453). Middle High German; ahsel; f; shoulder, armpit; 3; –; –; (80389). Middle Low German; asse; f; axle; 1; –; –; (80514). Modern Greek; ἄξων; m; axle; 1; –; –; (80571). Norwegian (Bokmål); akse; m; axis; 2; Loan; German; (80466). Norwegian (Bokmål); aksel; m; axle; 1; –; –; (80458). Norwegian (Bokmål); aksling; m; drive shaft; 3; –; –; (80457). Norwegian (Bokmål); oks; f; tip of the hub; 3; –; –; (80462). Norwegian (Nynorsk); akse; m; axis; 2; Loan; German; (80477). Norwegian (Nynorsk); aksel; m; axle; 1; –; –; (80473). Norwegian (Nynorsk); aksling; m; drive shaft; 3; –; –; (80472). Occitan; ais; m; axle, axis; 1; –; –; (80624). Old Church Slavonic; osь; f; axle; axis; 1; –; –; (80693). Old English; *eax; f; axle; 1; –; –; (80533). Old English; *eax-tréow; n; axle; axle-tree; 1; –; –; (80600). Old English; eaxl; f; armpit; 3; –; –; (80414). Old Frisian; axle, axele; f; axle; 1; –; –; (80417). Old High German; ahsa; f; axle, axis; 1; –; –; (80454). Old High German; ahsala, ahsla; f; shoulder; armpit; 3; –; –; (80390). Old Irish; ais; f; back; 3; –; –; (80555).

443

Old Norse; ǫxl; f; shoulder; 3; –; –; (80381). Old Norse; ǫxull; m; axle; 1; –; –; (80435). Old Norse; ǫxull-tré, öxul-tré; n; axle-tree; 1; –; –; (80587). Old Prussian; assis; f; axle; axis; 1; –; –; (80703). Old Saxon; ahsa; f; axle; 1; –; –; (80524). Old Saxon; ahsala, ahsla; f; shoulder, armpit; 3; –; –; (80407). Old Swedish; axul; m; axle; 1; –; –; (80438). Polish; oś; f; axle; 1; –; –; (80661). Portuguese; eixo; m; axle; axis; 1; –; –; (80637). Proto-Albanian; *akškā, *aškā; –; –; 0; –; –; (80580). Proto-Balto-Slavic; *aśis; –; –; 0; –; –; (80655). Proto-Celtic; *aksilā; –; axle; 0; –; –; (80558). Proto-Germanic; *ahse-; f; axle; 0; –; –; (80515). Proto-Germanic; *ahslō-; f; shoulder, armpit; 0; –; –; (80382). Proto-Germanic; *ahsō-; f; axle; 0; –; –; (80455). Proto-Germanic; *ahsula-; –; axle; 0; –; –; (80436). Proto-Indo-European; *aks-; –; axis; 0; –; –; (80581). Proto-Indo-European; *h₂eḱs-; –; –; 0; –; –; (80437). Proto-Indo-European; *h₂eḱs-(i-); –; axle, arm-pit; 0; –; –; (80433). Proto-Indo-European; *h₂eks-(i)l-eh₂-; –; –; 0; –; –; (80426). Proto-Indo-European; *h₂eḱs-eh₂-; –; –; 0; –; –; (80456). Proto-Indo-European; *h₂eḱ-so-; –; –; 0; –; –; (80583). Proto-Indo-European; *h₂eḱs-on-; –; –; 0; –; –; (80573). Proto-Indo-European; *sm-h₂eḱs-ih₂-; –; –; 0; –; –; (80577). Proto-Italic; *akselā-; –; arm-pit, wing; 0; –; –; (80650). Proto-Italic; *aksi-; –; axle; 0; –; –; (80432). Proto-Slavic; *ȏsь; f; axle, axis; 0; –; –; (80654). Romanian; osie; f; axle; 2; Loan; Slavic (branch); (80653). Russian; os’; f; axle; axis; 1; –; –; (80665). Sanskrit; ákṣa-; m; axle; axis; 1; –; –; (80584). Scottish Gaelic; acastair; m,f; axle-tree; 2; Loan; Middle English; (80611). Scottish Gaelic; aiseal, aisil; f; axle, axle-tree; axis; 2; Loan; Middle English; (80550). Serbian; ȏs; f; axle; 1; –; –; (80685). Serbian; osòvina; f; axle; 1; –; –; (80681). Slovene; ǫ̑s; f; axle; axis; 1; –; –; (80669). Spanish; eje; m; axle; 1; –; –; (80633). Swedish; axel; c; axle; 1; –; –; (80442). Vulgar Latin; *axalis; –; positioned on the axis; 0; –; –; (80620). Vulgar Latin; *axĕlla; f; armpit; 3; –; –; (80428). Vulgar Latin; *axilis; –; positioned on the axis; 0; –; –; (80629). Welsh; echel; f; axle; axis; 1; –; –; (80425).

444

Appendix 3b: Lexical data: Indo-European

OIr mol ‘axle’ (no etym.) (80706) Irish; An Mol Theas; m; the South Pole; 3; –; –; (80710). Irish; An Mol Thuaidh; m; the North Pole; 3; –; –; (80707). Irish; mol; m; hub, nave; pivot, shaft, spindle; 3; –; –; (80708). Old Irish; mol; m; axle or rotating shaft, esp. the shaft of a (horizontal?) mill-wheel; 1; –; –; (80709). Scottish Gaelic; mul; m; axle-tree, axis; the Pole; 1; –; –; (80713). < Cz napraviti ‘to set right’ (80716) Czech; náprava; f; axle; restoration, repairing; 1; –; –; (80717). Czech; napraviti; v; to set right, to repair; 0; –; –; (80718). < PIE *wert- ‘to spin, turn’ (80719) Breton; gwerzhid; f; spindle; 3; –; –; (80731). Croatian; vretèno; n; spindle; 3; –; –; (80746). Czech; vřeteno; n; spindle; 3; –; –; (80738). Irish; fearsaid; f; spindle; chariot shaft; axle, axle-tree; Belt of Orion; 3; –; –; (80721). Latin; vertere; v; to turn; 0; –; –; (80736). Middle Breton; guerzit; –; spindle; 3; –; –; (80732). Middle High German; wirtel; m; spinning-ring; 3; –; –; (80720). Old Church Slavonic; vrěteno; n; spindle; 3; –; –; (80750). Old Irish; fertas; f; distaff, spindle; pole, stake, chariot shaft; axletree, axle; 3; –; –; (80722). Polish; wrzeciono; n; spindle; 3; –; –; (80740). Proto-Indo-European; *wert-; –; –; 0; –; –; (80723). Russian; veretenó; n; spindle; 3; –; –; (80742). Sanskrit; vartulā-; n; circle; 3; –; –; (80752). Sanskrit; vṛt-; v; to turn; 0; –; –; (80754). Scottish Gaelic; feàrsaid; f; spindle; 3; –; –; (80724). Serbian; vretèno; n; spindle; 3; –; –; (80748). Slovene; vreteno; n; spindle; 3; –; –; (80744). Welsh; gwerthyd; f; spindle; 3; –; –; (80729). PAlb *bāsta- ‘spindle, axis’ (uct. etym.) (80764) Albanian (Tosk); bosht; m; spindle, axis, axle; 3; –; –; (80765). Proto-Albanian; *bāsta; –; –; 0; –; –; (80766). Uct. etym. (← IIr?) (80767) Tocharian B; ṣem; –; axle; 1; –; –; (80768). barley Gr ἀκοστή ‘barley’ (uct. etym.) (73604) Classical Greek; ἀκοστή; f; barley; 1; –; –; (73605). PIE *bhor-s- ‘barley (flour)’ (73606) Albanian (Tosk); bar; m; grass; 0; –; –; (73659). Breton; bara; m; bread; 0; –; –; (73647). Bulgarian; brašnó; n; flour; 3; –; –; (73677). Croatian; brȁšno; n; flour; 3; –; –; (73669). English; barley; –; hardy cereal of the genus Hordeum widely used as food and in malt

liquors and spirits such as whiskey; 1; –; –; (73610). Frisian; berre; –; barley; 1; –; –; (73632). Gothic; barizeins; adj; made of barley; 0; –; –; (73638). Latin; far; n; spelt; husked wheat, emmer; grain, flour, coarse meal; 3; –; –; (73657). Latvian; barĩba; f; food; 0; –; –; (73685). Middle Breton; bara; m; bread; 0; –; –; (73648). Middle English; bærlíc, barlic, barrliȝ, berley; –; barley; 1; –; –; (73611). Middle English; bere; –; barley; 1; –; –; (94226). Middle Welsh; bara; m; bread; 0; –; –; (73644). Old Church Slavonic; brašьno; n; food; 0; –; –; (73681). Old Cornish; bara; –; bread; 0; –; –; (73654). Old English; bærlíc; –; (of or pertaining to) barley; 0; –; –; (73612). Old English; bere, bær; m; barley; 1; –; –; (73613). Old Irish; bairgen; f; bread, loaf; food; 0; –; –; (73641). Old Norse; barr; n; grain, cereal; barley; 3; –; –; (73607). Proto-Albanian; *bara; –; –; 0; –; –; (73660). Proto-Balto-Slavic; *bar-; –; –; 0; –; –; (73663). Proto-Celtic; *barageno/ā-, *barago/ā-; –; (barley) bread; 0; –; –; (73642). Proto-Germanic; *bariz-, *barza-; n; barley; 0; –; –; (73608). Proto-Indo-European; *bhar-; –; barley; 0; –; –; (73643). Proto-Indo-European; *bhar-s-; –; barley; 0; –; –; (73658). Proto-Indo-European; *bhar-s-in-om; –; –; 0; –; –; (73664). Proto-Slavic; *bȍršьno; n; flour, food; 0; –; –; (73662). Serbian; brȁšno; n; flour; 3; –; –; (73673). Slovene; brášnọ; n; food; 0; –; –; (73665). Ukrainian; bórošno; n; ryemeal, rye flour; 3; –; –; (73661). PIE *bheuh₂-u- ‘barley’ < PIE *bheuh₂- ‘to grow, be’ (73688) Danish; byg; c; barley; 1; –; –; (73701). Elfdalian; begg-; m; barley; 1; –; –; (73721). English; bigg; –; hardy variety of barley grown mainly in northern England and Scotland; 1; –; –; (73728). Faroese; bygg; n; barley; 1; –; –; (73717). Icelandic; bygg; n; barley; 1; –; –; (73713). Middle English; big; –; barley; 2; Loan; Old Norse; (94225). Norwegian (Bokmål); bygg; m,n; barley; 1; –; –; (73705). Norwegian (Nynorsk); bygg; m,n; barley; 1; –; –; (73709). Old English; bēow; n; barley; cereal; 1; –; –; (73737). Old English; beowod; –; harvest; 0; –; –; (73740). Old Frisian; bē; n; barley; 1; –; –; (73743).

Appendix 3b: Lexical data: Indo-European

Old Norse; bygg; n; barley; cereal; 1; –; –; (73689). Old Saxon; beu; –; harvest; 0; –; –; (73725). Old Swedish; biug, biugh, biog; n; barley; 3; –; –; (73692). Proto-Germanic; *bewwa-; n; yield; barley; 0; –; –; (73690). Swedish; bjugg, bju, bygg, bägg; c; barley; 3; –; –; (73696). PIE *ghr̥-yo- ‘barley’ (73746) Albanian (Tosk); drithë; fpl; cereal, grain; wheat; 3; –; –; (73753). Catalan; ordi; m; barley; 1; –; –; (73798). Classical Greek; κριθή; f; grain of barley; barley; 3; –; –; (73750). Dutch; gerst; c; barley; 1; –; –; (73773). French; orge; f,m; barley; hulled barley; 1; –; –; (73789). German; Gerste; f; barley; 1; –; –; (73758). Hittite; karaš-; n; wheat, emmer-wheat; 3; –; –; (73755). Italian; orzo; m; barley; 1; –; –; (73783). Latin; hordeum; n; barley; 1; –; –; (73784). Middle Dutch; gerst, gerste, garst, gorste, geerst; f; barley; 1; –; –; (73774). Middle High German; gerste; f; barley; 1; –; –; (73759). Middle Low German; gerste, garste, gast; f; barley; 1; –; –; (73770). Modern Armenian; gari; –; wheat; 3; –; –; (73747). Modern Greek; κριθάρι; n; barley; 1; –; –; (73749). Occitan; òrdi; m; barley; cereal (generic); 1; –; –; (73786). Old High German; gersta; f; barley; 1; –; –; (73760). Old Saxon; gersta; f; barley; 1; –; –; (73780). Proto-Albanian; *ǵhr(i)sD-; –; –; 0; –; –; (73754). Proto-Armenian; *ghr̥yo-; –; –; 0; –; –; (73748). Proto-Germanic; *gerstō-; f; barley; 0; –; –; (73761). Proto-Italic; *χor(s)d-ejo-; –; barley; 0; –; –; (73785). Provençal; òrdi; m; barley; 1; –; –; (73801). Romanian; orz; n; barley; 1; –; –; (73795). PIE *yewh₁o- ‘barley’ (73806) Avestan; yava-; m; barley, corn, grain; 1; –; –; (73808). Hittite; eu̯an-; n; a kind of grain; 0; –; –; (73811). Lithuanian; ja˜vai; mpl; grain; 3; –; –; (73807). Persian; ǰow; –; barley; 1; –; –; (73809). Proto-Indo-European; *iéu-on-; –; –; 0; –; –; (73812). Sanskrit; yava-; m; barley; grain; 1; –; –; (73810). PSl *ęčьmy ‘barley’ (73813) Croatian; jȅčmēn; m; barley, sty (in the eye); 1; –; –; (73822). Czech; ječmen; m; barley; 1; –; –; (73814). Old Church Slavonic; jęčьmy; m; barley; 1; –; –; (73826).

445

Old Church Slavonic; ǫkotь; f; hook; 0; –; –; (73828). Polish; jęczmień; m; barley; 1; –; –; (73816). Proto-Slavic; *ęčьmy; m; barley; 0; –; –; (73815). Russian; jačmén’; m; barley, sty (in the eye); 1; –; –; (73818). Serbian; jȅčmēn; m; barley, sty (in the eye); 1; –; –; (73824). Slovene; ječmen; m; barley; 1; –; –; (73820). PIE *sh₁(e)s-yo- ‘grain, corn’ (73829) Breton; heiz; –; barley (collective); 1; –; –; (73833). Cornish; hêth, haiz; m; barley; 1; –; –; (73840). Gaulish; sasia, asia; –; rye; 3; –; –; (73843). Hittite; šēša-; –; fruit; harvest; 3; –; –; (73847). Middle Breton; heiz; –; barley; 1; –; –; (73834). Middle Welsh; heidd; m; barley; 1; –; –; (73830). Proto-Celtic; *sasyo-; –; barley; 0; –; –; (73831). Proto-Indo-European; *sh₁-s-, *sh₁es-; –; grain, corn; 0; –; –; (73832). Sanskrit; sasyá-; f; corn-field, corn, grain; 3; –; –; (73846). OIr eorna ‘barley’ (73848) Irish; eorna; f; barley; 1; –; –; (73849). Old Irish; eórna; f; barley; 1; –; –; (73850). Scottish Gaelic; eòrna; m; barley; 1; –; –; (73851). PIE *(H)meyǵ(h)- ‘barley, corn’ (73854) Latvian; maize; f; bread; 0; –; –; (73856). Latvian; mieži; mpl; barley; 1; –; –; (73855). Lithuanian; mie˜žiai; mpl; barley; 1; –; –; (73857). Lat cibus ‘food’ (73858) Catalan; civada; f; oats; 3; –; –; (73874). Italian; cibo; m; food; 0; Loan; Latin; (73859). Italian; civaia; f; dry foodstuff; 3; –; –; (73861). Latin; cibāre; v; to feed, to nourish; 0; –; –; (73872). Latin; cibaria; f; food; 0; –; –; (73862). Latin; cibus; m; food; 1; –; –; (73860). Latin; cĭbus; m; food; 0; –; –; (73873). Occitan; civada; f; oats; 3; –; –; (73864). Portuguese; cevada; f; barley (plant and grain); 1; –; –; (73869). Portuguese; cevo; m; food, nutricion; bait; 0; –; –; (73871). Spanish; cebada; f; fodder, barley; 3; –; –; (73866). Spanish; cebo; m; fodder, food; 3; –; –; (73867). PIE *h₂elbhi- ‘barley’ (73877) Albanian (Tosk); elb; m; barley; 1; –; –; (73880). Classical Greek; ἀλφι; n; barley-groats; 3; –; –; (73878). Proto-Albanian; *albi; –; –; 0; –; –; (73881). Proto-Indo-European; *h₂elbhi-; –; barley; 0; –; –; (73879). No etym. (–) Middle Persian; ǰaw; –; barley; 1; –; –; (94010). bear PIE *médhu- ‘honey, mead’ (61738) Albanian (Tosk); meçkë; f; female bear; 2; Loan; Croatian; (62256).

446

Appendix 3b: Lexical data: Indo-European

Bulgarian; méčka; f; bear (generic); female bear; 1; –; –; (62284). Croatian; mȅčka; f; bear; 1; –; –; (62257). Croatian; mèdvjed; m; bear; 1; –; –; (62270). Czech; medvěd; m; bear; 1; –; –; (62258). Old Church Slavonic; medvědь; m; bear; 1; –; –; (62287). Polish; niedźwiedź; m; bear; 3; –; –; (62261). Proto-Indo-European; *medhu-h₁ed-; –; –; 0; –; –; (62260). ̀ Proto-Slavic; *medvědь; m; bear; 0; –; –; (62259). Russian; medvéd’; m; bear; 1; –; –; (62264). Sanskrit; madhvád-; m; honey-eater; 3; –; –; (62290). Serbian; mȅčka; f; bear; 1; –; –; (62280). Serbian; mèdvjed; m; bear; 1; –; –; (62277). Slovene; médvẹd; m; bear; 1; –; –; (62267). PIE *h₂rtḱo- ‘bear’ (62148) Albanian (Tosk); arí; m; bear; 1; –; –; (62223). Avestan; arša-; m; bear; 1; –; –; (62233). Breton; arzh; m; bear; 1; –; –; (62159). Catalan; os; m; bear; 0; –; –; (27066). Classical Greek; ἄρκτος; f,m; bear; Ursa maior; 1; –; –; (62221). French; ours; m; bear; 1; –; –; (62164). Friulian; ors; m; bear; 1; –; –; (62213). Gaulish; *art-; –; bear; 1; –; –; (62169). Gaulish; Artio; –; –; 0; –; –; (62168). Hindi; rīch, rīchin, rīchnī; m,f; bear; 1; –; –; (62240). Hittite; ḫartakka-; c; bear; 1; –; –; (62244). Italian; orso; m; bear; 1; –; –; (62172). Kurdish (Kurmanji); hirç; f; bear; 2; Loan; Modern Armenian; (62227). Kurdish (Sorani); wirç; –; bear; 2; Loan; Modern Armenian; (62230). Latin; ursus; m; bear; 1; –; –; (62173). Middle Breton; ours; –; bear; 2; Loan; French; (62163). Middle Welsh; arth; m,f; bear; 1; –; –; (62153). Modern Armenian; arǰ; –; bear; 1; –; –; (62220). Occitan; ors; m; bear; 1; –; –; (62180). Old Breton; arth-; –; bear; 1; –; –; (62160). Old French; urs; m; bear; 1; –; –; (62185). Old Irish; art; m; bear; hero, warrior; 1; –; –; (62149). Persian; xers; –; bear; 1; –; –; (62235). Portuguese; urso; m; bear; 1; –; –; (62197). Proto-Albanian; *ara; –; –; 0; –; –; (62225). Proto-Albanian; *arina; –; –; 0; –; –; (62224). Proto-Celtic; *arto-; –; bear; 0; –; –; (62150). Proto-Indo-European; *h₂rtḱo-; –; bear; 0; –; –; (62151). Proto-Indo-Iranian; *Hrtća-; –; –; 0; –; –; (62236). Proto-Italic; *orsso-?; –; –; 0; –; –; (62174). Provençal; ors; m; bear; 1; –; –; (62209). Punjabi; ricch; m; bear; 1; –; –; (62242). Romanian; urs; m; bear; 1; –; –; (62201). Sanskrit; ŕ̥kṣa-; m; bear; 1; –; –; (62238). Sardinian; ursu; m; bear; 1; –; –; (62176).

Spanish; oso; m; bear; 1; –; –; (62193). Welsh; arth; m,f; bear; 1; –; –; (62152). OIr math ‘bear’ (uct. etym.) (62245) Irish; mathúin; m; bear; 1; –; –; (62246). Middle Irish; mathgamain; m; bear; 1; –; –; (62247). Old Irish; math; m; bear; 1; –; –; (62249). Old Irish; mathgamain; m; bear; 1; –; –; (62248). Scottish Gaelic; mathan; m; bear; 1; –; –; (62250). PIE *bhero- ‘the brown one’ (62291) Bengali; bhāluk; –; bear; 1; –; –; (62421). Danish; bjørn; c; bear; 1; –; –; (62383). Dutch; beer; m; bear; 1; –; –; (62324). Elfdalian; byönn; m; bear; 1; –; –; (62408). English; bear; –; large heavy mammal of the animal Ursidae; 1; –; –; (62333). Faroese; bjørn; f; bear; 1; –; –; (62403). German; Bär; m; bear; 1; –; –; (62305). Hindi; bhāl, bhālūx˘ k; m; bear; 1; –; –; (62420). Icelandic; bera; f; female bear; 1; –; –; (62300). Icelandic; björn; m; bear; 1; –; –; (62398). Irish; béar; m; bear; 2; Loan; English; (62354). Irish; beithir; f; bear; warrior (literary); 1; –; –; (62348). Lithuanian; béras; adj; brown; 0; –; –; (62366). Middle Dutch; bere, beer; m; bear; 1; –; –; (94212). Middle English; bere; –; bear; 1; –; –; (62334). Middle High German; ber, bēr; m; bear; 1; –; –; (62306). Middle Low German; bere; f; bear; 1; –; –; (62320). Norwegian (Bokmål); bjørn; m; bear; 1; –; –; (62388). Norwegian (Nynorsk); bjørn; m; bear; 1; –; –; (62393). Old English; beorn; m; warrior, prince; 0; Loan; Old Norse; (62413). Old English; bera; m; bear; 1; –; –; (62335). Old High German; bero; m; bear; 1; –; –; (54921). Old Irish; beithir; f; bear; warrior; 2; Loan; Old English; (62349). Old Norse; bera; f; female bear; 1; –; –; (62292). Old Norse; birna; f; female bear; 1; –; –; (62296). Old Norse; bjǫrn; m; bear; 1; –; –; (62368). Old Swedish; biörn, biorn; m; bear; 1; –; –; (62372). Proto-Germanic; *beran-; m; bear; 0; –; –; (62293). Proto-Germanic; *bernjōn-; –; female bear; 0; –; –; (62297). Proto-Germanic; *bernu-; –; bear; 0; –; –; (62369). Proto-Indo-European; *bherH-on-; –; –; 0; –; –; (62294). Proto-Indo-European; *bhero-; –; brown; 0; –; –; (62295). Sanskrit; bhallūx´ ka-; m; bear; 1; –; –; (62419). Swedish; björn; c; bear; 1; –; –; (62377).

Appendix 3b: Lexical data: Indo-European

BSl *talk-, *tlāk- ‘bear’ < PIE *tel-k- ‘to push, to hit’ (62423) Latvian; lācis; m; bear; 1; –; –; (62424). Lithuanian; lokys; m; bear; 1; –; –; (62427). Old Prussian; clokis, klokis; m; bear; 1; –; –; (62430). Proto-Balto-Slavic; *talk-, *tlāk-; –; –; 0; –; –; (62425). Proto-Indo-European; *tel-k-, *tl-ek-; v; to push, hit, kick, trample; 0; –; –; (62426). bee PIE *meli- ‘honey’ (61480) Albanian (Tosk); bletë; f; bee; beehive; 2; Loan; Vulgar Latin; (61724). Albanian (Tosk); mjalcë; f; bee; 1; –; –; (61491). Classical Greek; μέλι; n; honey; 0; –; –; (61486). Classical Greek; μέλισσα, μέλιττα; f; bee; 1; –; –; (61485). Latin; mel; n; honey; (by extension) sweetness, sweet talk, delight; 0; –; –; (61727). Latin; mellarium; n; beehive, apiary; 0; –; –; (61726). Modern Armenian; mełr; –; honey; 0; –; –; (61482). Modern Armenian; meɫu; –; bee; 1; –; –; (61481). Modern Greek; μέλισσα; f; bee; 1; –; –; (61484). Proto-Albanian; *melitjā; –; –; 0; –; –; (61492). Proto-Indo-European; *mel-; –; –; 0; –; –; (61483). Proto-Indo-European; *meli-; –; honey; 0; –; –; (61729). Proto-Indo-European; *meli-t-, *melit-; –; honey; 0; –; –; (61487). Proto-Italic; *meli-; –; –; 0; –; –; (61728). Vulgar Latin; *melettum; –; beehive (?); 0; –; –; (61725). Gm *biōn ‘bee’ (uct. etym.) (61494) Bulgarian; pčelá; f; bee; 1; –; –; (61631). Croatian; pčèla, čèla; f; bee; 1; –; –; (61623). Czech; včela; f; bee; 1; –; –; (61607). Danish; bi; c; bee; 1; –; –; (61507). Dutch; bij; c; bee; 1; –; –; (61557). Elfdalian; bi; n; bee; 1; –; –; (61531). Elfdalian; bia; f; bee; 1; –; –; (61527). English; bee; –; stinging insect of the genus Apis, which collects pollen and makes honey; 1; –; –; (61567). Faroese; býfluga; f; bee; 1; –; –; (61523). Gaulish; *biko-; –; bee; 1; –; –; (61603). German; Biene; f; bee; 1; –; –; (61535). Icelandic; býfluga; f; bee; 1; –; –; (61519). Irish; beach; f; bee; 1; –; –; (61584). Irish; beach ghabhair; f; wasp (lit. goat bee); 3; –; –; (61588). Irish; beachán; m; wasp; 3; –; –; (61583). Latin; fūcus; m; drone (bee); 3; –; –; (61580). Latvian; bite; f; bee; 1; –; –; (61639). Lithuanian; bìtė; f; bee; 1; –; –; (61642). Middle Dutch; bie; f; bee; 1; –; –; (61558). Middle English; be; –; bee; 1; –; –; (61568).

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Middle High German; bin, bine; f; bee; 1; –; –; (61536). Middle Low German; bene, beine; f; bee; 1; –; –; (61551). Middle Low German; bîe, beie; f; bee; 1; –; –; (61554). Middle Welsh; begegyr, bygegyr; m; drone; 3; –; –; (61600). Norwegian (Bokmål); bie; m,f; bee; 1; –; –; (61511). Norwegian (Nynorsk); bie; f; bee; 1; –; –; (61515). Old Church Slavonic; bьčela, bъčela; f; bee; 1; –; –; (61635). Old English; bēo; f; bee; 1; –; –; (61569). Old High German; bīa; f; bee; 1; –; –; (61548). Old High German; bini; n; bee; 1; –; –; (61537). Old Irish; bech; m,f; bee; 1; –; –; (61585). Old Norse; bý; n; bee; 1; –; –; (61495). Old Prussian; bitte; f; bee; 1; –; –; (61645). Old Saxon; bī; f; bee; 1; –; –; (61564). Old Swedish; bī, by; n; bee; 1; –; –; (61498). Polish; pszczoɫa; f; bee; 1; –; –; (61611). Proto-Balto-Slavic; *bi-t-, *bi-kel-eh₂; –; –; 0; –; –; (61609). Proto-Celtic; *biko-; –; bee; 0; –; –; (61586). Proto-Germanic; *bini; –; bee; 0; –; –; (61529). Proto-Germanic; *bîôn-, *biôn-; –; bee; 0; –; –; (61496). Proto-Indo-European; *bhi-; –; –; 0; –; –; (61497). Proto-Indo-European; *bhi-ko-; –; bee; 0; –; –; (61587). Proto-Indo-European; *bhoy-ko-; –; –; 0; –; –; (61581). Proto-Slavic; *bьčelà; f; bee; 0; –; –; (61608). Russian; pčelá; f; bee; 1; –; –; (61615). Scottish Gaelic; beach; m; bee; 1; –; –; (61593). Serbian; pčèla; f; bee; 1; –; –; (61627). Slovene; čebę̑la; f; bee; 1; –; –; (61619). Swedish; bi; n; bee; 1; –; –; (61502). PCelt *gʷan-o- ‘to strike’, ‘bee’ < PIE *gʷhen‘to strike’ (61648) Breton; gwenanenn; –; bee; 1; –; –; (61654). Middle Breton; guenannen; –; bee; 1; –; –; (61655). Old Cornish; guenenen; –; bee; 1; –; –; (61661). Old Cornish; gwane; v; to thrust, to stick, to stab; 0; –; –; (61662). Proto-Celtic; *gwan-o-; v; to strike, kill; 0; –; –; (61652). Proto-Indo-European; *gʷhen-; v; to strike, slay; 0; –; –; (61653). Welsh; gwan; v; to thrust, to stick, to stab; 0; –; –; (61651). Welsh; gwenyn; coll; bees; 1; –; –; (61650). Welsh; gwenynen; sg; bee; 1; –; –; (61649). OIr teillén ‘swarm of bees’ (61665) Irish; seileán; m; wild bee; 1; –; –; (61666). Irish; teileán; m; wasp; 3; –; –; (61668). Old Irish; teillén, -teillén; m; swarm of bees; 3; –; –; (61667).

448

Appendix 3b: Lexical data: Indo-European

Scottish Gaelic; seillean; m; bee, heath or fieldbee; 1; –; –; (61671). Scottish Gaelic; teillean; –; bee; 1; –; –; (61673). Welsh; chwil; m,f; beetle, chafer; 3; –; –; (61677). Welsh; telyn; –; harp; 0; –; –; (61676). PItal *api- ‘bee’ (61678) Catalan; abella; f; bee; 1; –; –; (61706). French; abeille; f; bee; 1; –; –; (61694). Italian; ape; f; bee; 1; –; –; (61679). Italian; pecchia; f; bee; 3; –; –; (61686). Latin; apicula; f; bee; 1; –; –; (61687). Latin; apis; f; bee; 1; –; –; (61680). Occitan; abelha; f; bee; 1; –; –; (61690). Old French; ef; m,f; bee; 1; –; –; (61682). Portuguese; abelha; f; bee; 1; –; –; (61702). Proto-Italic; *api-?; –; –; 0; –; –; (61681). Provençal; abeiho; f; bee; 1; –; –; (61710). Spanish; abeja; f; bee; 1; –; –; (61698). Lat alvus ‘belly, beehive’ < PIE *h₂eulo- ‘tube, cavity’ (61717) Late Latin; alvina; –; beehive; 0; –; –; (61719). Latin; alvus; f; belly, beehive; 0; –; –; (61720). Proto-Indo-European; *h₂eulo-; –; tube, cavity; 0; –; –; (61722). Proto-Italic; *aulos; –; –; 0; –; –; (61721). Romanian; albină; f; bee; 1; –; –; (61718). Skt alin- ‘bee, scorpion’ (uct. etym.) (61730) Hindi; ālī; m; scorpion, bumblebee; 3; –; –; (61732). Sanskrit; alin-; m; black bee, scorpion; 3; –; –; (61731). Skt bhramará- < bhram- ‘to flicker’ (61733) Bengali; bhramara, bhomar, bhomrā; –; bee, bumble-bee; 1; –; –; (61736). Hindi; bhaũr, bhaur, bhaũrā; m; large black bee; 3; –; –; (61735). Punjabi; bhãvar, bhãvarā, bhaur, bhaurā, bhaũrā; m; black bee; 3; –; –; (61737). Sanskrit; bhramará-; m; large black bee; 3; –; –; (61734). PIE *médhu- ‘honey, mead’ (61738) Sanskrit; madhu-lih-; m; bee (lit. “honey-licker”); 1; –; –; (61739). IIr *makš- ‘fly, bee’ (uct. etym.) (61741) Hindi; madhumakkhī; f; bee; 1; –; –; (61743). Punjabi; makhī, makkh; f; bee; also horsefly, gnat, any stinging fly; 1; –; –; (61745). Sanskrit; mákṣā-, mákṣ-; f; fly; 3; –; –; (61742). CT kro(ṅ)kśe* ‘bee’ (uct. etym.) (61747) Tocharian A; kroṅśe*; –; bee; 2; Loan; Tocharian B; (61748). Tocharian B; kro(ṅ)kśe*; –; bee; 1; –; –; (61749). beech PIE *bheh2ǵ- ‘beech’ (43499) Catalan; faig; m; beech; 1; –; –; (43504). Classical Greek; φηγός; f; oak, Quercus aegilops; 3; –; –; (43506). Danish; bøg; c; beech; 1; –; –; (43518). Dutch; beuk; c; beech; 1; –; –; (43524). English; beech; –; beech; 1; –; –; (43515). Faroese; bók; f; beech; 1; –; –; (43521).

Gaulish; *bāgos; –; beech; 1; –; –; (43505). German; Buche; f; beech; 1; –; –; (43513). Icelandic; beyki; n; beech; 1; –; –; (43520). Latin; fāgus; f; beech; 1; –; –; (43501). Middle Dutch; boeke; f; beech; 1; –; –; (43523). Middle English; beche; –; beech; 1; –; –; (43514). Middle High German; buoche; f; beech; 1; –; –; (43512). Middle Low German; bōke; –; beech; 1; –; –; (43522). Norwegian (Bokmål); bøk; m; beech; 1; –; –; (43519). Old English; bōc, bēce; f; beech; 1; –; –; (43509). Old High German; buohha; f; beech; 1; –; –; (43511). Old Norse; bók; f; beech; 1; –; –; (43508). Old Saxon; bōka; f; beech; 1; –; –; (43510). Old Swedish; bōk; f; beech; 1; –; –; (43516). Portuguese; faia; f; beech; 1; –; –; (43502). Proto-Germanic; *bōk(j)ō-; f; beech; 0; –; –; (43507). Proto-Indo-European; *bheh₂ǵ-; –; beech; 0; –; –; (43499). Proto-Italic; *fāgo-; –; beech; 0; –; –; (43500). Spanish; haya; f; beech; 1; –; –; (43503). Swedish; bok; c; beech; 1; –; –; (43517). PIE *h₃es-n- ‘ash tree’ (43525) Albanian (Tosk); ah; m; beech; 1; –; –; (43533). Classical Greek; ὀξύα -η; f; beech, Fagus silvatica; spear shaft (made of beech wood), spear; 1; –; –; (43535). birch PCelt *betu- ‘birch’ < PIE *gʷet-u- ‘pitch, resin’ (43718) Catalan; bedoll; m; birch; 1; –; –; (43735). Cornish; besowen; f; birch; 1; –; –; (43727). French; bouleau; m; birch; 1; –; –; (43732). Gaulish; *betyo-; –; birch; 1; –; –; (43724). Italian; betulla; f; birch; 1; –; –; (43733). Latin; betulla; f; birch; 2; Loan; Gaulish; (43728). Middle Breton; bezu, bezv-en; –; birch; 1; –; –; (43722). Middle Welsh; bedw-en; f; birch; 1; –; –; (43721). Old Cornish; bedewen; –; birch (?); 1; –; –; (43723). Old French; boul; m; birch; 1; –; –; (43731). Old Irish; beithe; m; birch; 1; –; –; (43720). Portuguese; bétula; f; birch; 1; –; –; (43734). Proto-Celtic; *betu-; –; birch; 0; –; –; (43719). Proto-Indo-European; *gwet-u-; –; pitch, resin; 0; –; –; (43718). Spanish; abedul; m; birch; 1; –; –; (43730). Spanish; biezo; m; birch; 2; Loan; Gaulish; (43736). PIE *bhrHǵ- ‘birch tree’ (53958) Latin; fraxinus; f; ash tree; 1; –; –; (43674). Bulgarian; brezá; f; birch; 1; –; –; (43656). Czech; bříza; f; birch; 1; –; –; (43649). Dutch; berk; c; birch; 1; –; –; (43669). English; birch; –; birch; 1; –; –; (43671). Latvian; bę̃rzs; m; birch; 1; –; –; (43643).

Appendix 3b: Lexical data: Indo-European

Lithuanian; béržas; m; birch; 1; –; –; (43642). Middle Dutch; berk, berke, bjirk, birke; m,f; birch; 1; –; –; (43665). Middle English; birche; –; birch; 1; –; –; (43670). Old Church Slavonic; brěza; f; birch; 1; –; –; (43646). Old English; berc, beorc; f; birch; 1; –; –; (43664). Old English; bierce, byrce, birce, birciae; f; birch; 1; –; –; (43672). Old Norse; bjǫrk; f; birch; 1; –; –; (43663). Old Prussian; berse; f; birch; 1; –; –; (43644). Polish; brzoza; f; birch; 1; –; –; (43650). Proto-Balto-Slavic; *bérʔźos; *bérʔźaʔ; –; birch; 0; –; –; (43641). Proto-Germanic; *berkō-; f; birch; 0; –; –; (43640). Proto-Indo-Aryan; *bhergo-, *bhergā-; –; birch; 0; –; –; (43658). Proto-Slavic; *bèrza; f; birch; 0; –; –; (43645). Russian; berëza; f; birch; 1; –; –; (43648). Sanskrit; bhūrjá-; m; kind of birch; 3; –; –; (43660). Serbo-Croatian; brȅza; f; birch; 1; –; –; (43651). Slovene; brẹ́za; f; birch; 1; –; –; (43654). bison Gr βόνασος ‘aurochs, wisent’ (uct. etym.) (64164) Classical Greek; βόνασ(σ)ος; m; aurochs; wisent, (European) bison; 1; –; –; (64165). Gr βόλινθος ‘aurochs, wisent’ (uct. etym.) (64166) Classical Greek; βόλινθος; m; aurochs; wisent, (European) bison; 1; –; –; (64167). Proto-form *tsomb(h)-, *dzomb(h)- (uct. etym.) (64168) Bulgarian; zúbǎr; m; wisent, (European) bison; 1; –; –; (64186). Croatian; zùbār; m; wisent, (European) bison; 1; –; –; (64182). Czech; zubr; m; wisent, (European) bison; 1; –; –; (64174). English; zubr; –; wisent, (European) bison; 2; Loan; Russian; (64169). Latvian; sum̃ brs, stumbrs, stumbris, sũbrs; m; aurochs; 3; –; –; (64188). Lithuanian; stum̃ bras; m; wisent, (European) bison; aurochs; 1; –; –; (64190). Old Prussian; wissambs’, wissambris; –; aurochs; 3; –; –; (64197). Ossetian (Iron); dombaj; –; wisent, (European) bison; 1; –; –; (64192). Polish; żubr; m; wisent, (European) bison; 1; –; –; (64176). Proto-Slavic; *zǫbrъ; m; wisent; 0; –; –; (64171). Romanian; zimbru; m; visent, (European) bison; 2; Loan; Slavic (branch); (64172). Russian; izjúbr; m; red deer; 0; –; –; (64195). Russian; zubr; m; wisent, (European) bison; 1; –; –; (64170). Serbian; zùbār; m; wisent, (European) bison; 1; –; –; (64184). Slovene; zóber; m; wisent, (European) bison; 1; –; –; (64180).

449

Proto-form *uisond-, *uisondh- (uct. etym.) (64199) Classical Greek; βίσων, -ωνος; m; wisent, (European) bison; 2; Loan; Latin; (64318). Danish; bison; c; wisent, (European) bison; 2; Loan; Latin; (64280). Danish; visent; c; wisent, (European) bison; 2; Loan; German; (64210). Dutch; wisent; c; wisent, (European) bison; 1; –; –; (64253). English; bison; –; wild and shaggy-haired ox of the genus Bison; Bison bonasus, native to Europe; 2; Loan; Latin; (64286). English; wisent; –; the European bison, Bison bonasus or Bison wisent; 2; Loan; German; (64260). Faroese; visundur; m; wisent, (European) bison; 1; –; –; (64233). French; bison; m; bison; 1; –; –; (64303). German; Wisent; m; bison; 1; –; –; (64205). Gothic; wisund; m; wisent, (European) bison; 1; –; –; (64269). Icelandic; vísundur; m; wisent, (European) bison; 1; –; –; (64228). Irish; bíosún; m; bison; 2; Loan; English; (64293). Italian; bisonte; m; bison; 1; –; –; (64297). Latin; bisōn, -ontis; m; wisent, (European) bison; 2; Loan; Germanic (branch); (64272). Middle Dutch; wisent, wesent; m; wisent, (European) bison; 1; –; –; (64254). Middle English; bison, bisontes; –; wisent, (European) bison; 2; Loan; Latin; (64287). Middle High German; wisant, wisent, wisen; m; bison; 1; –; –; (64206). Middle Low German; wisent, wesent; m; wisent, (European) bison; 1; –; –; (64201). Modern Greek; βίσονας; m; bison; 1; –; –; (64317). Norwegian (Bokmål); bison; m; wisent, (European) bison; 2; Loan; Latin; (64282). Norwegian (Bokmål); visent; m; wisent, (European) bison; 2; Loan; German; (64216). Norwegian (Nynorsk); bison; m; wisent, (European) bison; 2; Loan; Latin; (64284). Norwegian (Nynorsk); visent; m; wisent, (European) bison; 2; Loan; German; (64222). Occitan; bison; m; bison; 1; –; –; (64300). Old English; wesend, weosend; m; wisent, (European) bison; 1; –; –; (64266). Old French; bison; m; wisent, (European) bison; 1; –; –; (64306). Old High German; wisunt, wisant; m; bison; 1; –; –; (64207). Old Norse; vísundr; m; wisent, (European) bison; 2; Loan; Middle Low German; (64200). Portuguese; bisão, bisonte; m; bison; 1; –; –; (64312). Proto-Germanic; *wisand-; m; wisent; 0; –; –; (64273). Proto-Germanic; *wisund-; m; wisent; 0; –; –; (64202).

450

Appendix 3b: Lexical data: Indo-European

Spanish; bisonte; m; bison; 1; –; –; (64309). Swedish; bison; c; wisent, (European) bison; 2; Loan; Latin; (64275). Swedish; bisonoxe; c; wisent, (European) bison; 1; –; –; (64278). Swedish; visent; c; wisent, (European) bison; 2; Loan; German; (64204). bow < PIE *bhewg(h)- ‘bend’ (87653) Breton; boug; adj; tender; 0; –; –; (87658). Danish; bue; c; bow; 1; –; –; (87693). Dutch; boog; c; bow; 1; –; –; (87745). Elfdalian; bugi; m; bow; 1; –; –; (87722). English; bow; –; device for shooting arrows; rod with horsehair used for playing certain stringed instruments; kind of knot; 1; –; –; (87758). Faroese; bogi; m; bow; 1; –; –; (87718). German; Bogen; m; bow; 1; –; –; (87726). Icelandic; bogi; m; bow; 1; –; –; (87714). Irish; bogha; m; bow; 1; –; –; (87781). Middle Breton; boug; adj; tender; 0; –; –; (87659). Middle Dutch; boge, booghe; m; bow; 1; –; –; (87746). Middle English; bow, boȝe, bowe; –; bow; arc, arch; 1; –; –; (87759). Middle English; bowe; –; bow; 1; –; –; (87800). Middle High German; boge; m; bow; 1; –; –; (87727). Middle Low German; boge; m; bow; 1; –; –; (87741). Middle Welsh; bwa; m; bow; 2; Loan; Middle English; (87799). Norwegian (Bokmål); boge; m; bow; 1; –; –; (87698). Norwegian (Bokmål); bue; m; bow; 2; Loan; Danish; (87703). Norwegian (Nynorsk); boge; m; bow; 1; –; –; (87709). Old Breton; buc; adj; rotten; 0; –; –; (87660). Old English; boga; m; bow; arc, arch; 1; –; –; (87760). Old Frisian; boga; m; bow; 1; –; –; (87773). Old High German; bogo; m; bow; 1; –; –; (87728). Old Irish; boga, bogha; m; bow; 2; Loan; Old Norse; (87782). Old Norse; bogi; m; bow; 1; –; –; (87671). Old Saxon; bogo; m; bow; 1; –; –; (87754). Old Swedish; boghi; m; bow; 1; –; –; (87675). Proto-Celtic; *buggo-; adj; soft, tender; 0; –; –; (87656). Proto-Germanic; *beugan-, *būgan-; v; to bow, bend; 0; –; –; (87673). Proto-Germanic; *bugan-; m; bow; 0; –; –; (87672). Proto-Indo-European; *bhéugh-; –; –; 0; –; –; (87812). Proto-Indo-European; *bhéugh-e-; –; –; 0; –; –; (87674).

Proto-Indo-European; *bhewg(h)-; –; to bend; 0; –; –; (87657). Sanskrit; bhuj-; v; to bend; 0; –; –; (28224). Scottish Gaelic; bogha; m; bow; 1; –; –; (87787). Swedish; båge; c; bow; 1; –; –; (87680). Swedish; pilbåge; c; bow; 1; –; –; (87686). Welsh; bwa; m; bow; 1; –; –; (87798). < PIE *weyh₁-ro- ‘turned, twisted’ (87813) Breton; gwar; adj; bent, curved; 0; –; –; (87830). Breton; gwareg; f; bow; 1; –; –; (87829). Cornish; gwarek; m; bow, arc, arch, crescent; 1; –; –; (87838). Cornish; gwarr; f; curve; 3; –; –; (87841). Irish; fiar; adj,m; bent, warped, crooked, perverse; bend, warp, twist, kink; 0; –; –; (87814). Middle Breton; goar; adj; curved; 0; –; –; (87831). Middle Breton; goarec; –; bow; 1; –; –; (87834). Middle Welsh; gwyr; adj; crooked; 0; –; –; (87826). Old Irish; fíar; adj; crooked; 0; –; –; (87815). Proto-Celtic; *wēro-; –; crooked; 0; –; –; (87816). Proto-Indo-European; *weyh₁-ro-; –; turned, twisted; 0; –; –; (87817). Scottish Gaelic; fiar; adj; bent, crooked, curved; 0; –; –; (87819). < PIE *gʷieh₂- ‘string’ (87844) Avestan; ǰyiā-; f; bowstring; 3; –; –; (87847). Classical Greek; βιός; m; bow, bowstring; 1; –; –; (87845). Proto-Indo-European; *gʷieh₂-; –; string; 0; –; –; (87846). Sanskrit; jyā́-, jiyā́-; f; bowstring; 3; –; –; (87849). Gr τόξον ‘bow’, Lat taxus ‘yew-tree’ (87851) Classical Greek; τόξον; n; bow; 1; –; –; (87853). Modern Greek; τόξο; n; bow; 1; –; –; (87852). Persian; taχš; –; (cross)-bow, arrow; 3; –; –; (87856). Arm aɫeɫn ‘bow; rainbow’ (uct. etym.) (87857) Modern Armenian; aɫeɫn; –; bow; rainbow; 1; –; –; (87858). Skt dhanvan- ‘bow’ (uct. etym.) (87859) Avestan; ϑanvan-, ϑanvar-; n; bow; 1; –; –; (87860). Old Persian; θanuvaniya-; –; archer, bowman; 0; –; –; (87861). Sanskrit; dhanvan-; n; bow; 1; –; –; (87862). PSl *lǫ̑kъ ‘bow’ (87864) Bulgarian; lăk; m; bow; 1; –; –; (87883). Croatian; lȗk; m; bow (between cart-shafts), bow (archery); 1; –; –; (87877). Czech; luk; m; bow; 1; –; –; (87865). Latvian; loks; m; arc, arch, bow, shaft-bow, rim; 3; –; –; (87889). Lithuanian; lañkas; m; bow (between cart-shafts), hoop (of a barrel), bend (in a road), bow (archery), circle; 1; –; –; (87891). Old Church Slavonic; lǫkъ; m; bow; 1; –; –; (87886). Old Prussian; lunkis; –; corner; 0; –; –; (87893). Polish; łuk; m; bow, arc, arch; 1; –; –; (87868).

Appendix 3b: Lexical data: Indo-European

Proto-Balto-Slavic; *lonkos; –; –; 0; –; –; (87867). Proto-Slavic; *lǫ̑kъ; m; bow; 0; –; –; (87866). Russian; luk; m; bow; 1; –; –; (87871). Serbian; lȗk; m; bow (between cart-shafts), bow (archery); 1; –; –; (87880). Slovene; lók; m; shaft-bow, bow, rainbow; 3; –; –; (87874). TB wäntalyi < TB wänt- ‘to wind, twist’ (87895) Proto-Indo-European; *wendh-; v; to wind; 0; –; –; (87898). Tocharian B; wänt-; v; to wind, to twist; 0; –; –; (87897). Tocharian B; wäntalyi; –; bow(-string); 1; –; –; (87896). PIE *ark-uh₂- ‘bow, arrow’ (87899) Albanian (Tosk); ark; m; bow; arch; 2; Loan; Latin; (87926). Catalan; arc; m; bow, arc, arch; 1; –; –; (87921). French; arc; m; bow, arc, arch; 1; –; –; (87909). Italian; arco; m; bow, arc, arch; 1; –; –; (87900). Latin; arcus; m; bow; arch; 1; –; –; (87901). Occitan; arc; m; bow; 1; –; –; (87906). Portuguese; arco; m; bow, arc, arch; 1; –; –; (87915). Romanian; arc; n; bow, arc, arch; 1; –; –; (87918). Sardinian; arcu; m; bow; 1; –; –; (87903). Spanish; arco; m; bow, arc, arch; 1; –; –; (87912). No etym. (–) Old Persian; vaça-; –; bow; 1; –; –; (94001). bull PIE *tawro- ‘bull, aurochs’ (54195) Albanian (Tosk); ter; m; bull; 1; –; –; (43493). Breton; tarv, tarw; m; bull; 1; –; –; (43621). Bulgarian; tur; m; aurochs; 3; –; –; (43486). Catalan; toro; m; bull; 1; –; –; (54226). Classical Greek; ταῦρος; m; bull; 1; –; –; (43475). Cornish; tarow; m; bull; 1; –; –; (43617). Croatian; tûr; m; aurochs; 3; –; –; (43484). Czech; tur; m,f; aurochs; 3; –; –; (43480). Elfdalian; tiųor; n; erect penis; hard, dark rings in conifer wood; 0; –; –; (43590). Faroese; tarvur; m; bull; 1; –; –; (54321). Faroese; tjórur; m; bullock, castrated bull, steer; 3; –; –; (43589). French; taureau; m; bull; 1; –; –; (54208). Gaulish; taruos; –; bull; 1; –; –; (43618). Gaulish; Tarvisium; –; –; 0; –; –; (54363). Icelandic; tarfur; m; bull; 1; –; –; (54313). Irish; tarbh; m; bull; 1; –; –; (43622). Italian; toro; m; bull; 1; –; –; (54202). Latin; taurus; m; bull; 1; –; –; (43472). Latvian; tàurs; m; aurochs; 3; –; –; (43488). Lithuanian; taũras; m; aurochs; 3; –; –; (43489). Middle Breton; taru; –; bull; 1; –; –; (43620). Middle Welsh; tarw; m; bull; 1; –; –; (43615). Modern Greek; ταύρος; m; bull; 1; –; –; (54196). Norwegian (Bokmål); tyr; m; bull; 1; –; –; (43586). Norwegian (Nynorsk); tyr; m; bull; 1; –; –; (43587). Occitan; taur; m; bull; 1; –; –; (54205). Old Breton; taruu; –; bull; 1; –; –; (43616).

451

Old Church Slavonic; turъ; m; bull; 1; –; –; (43487). Old French; tor; m; bull; 1; –; –; (54210). Old French; torel, toreau; m; bull, young bull; 1; –; –; (54209). Old Irish; tarb; m; bull; 1; –; –; (43614). Old Norse; tarfr; m; bull; 2; Loan; Old Irish; (54290). Old Norse; þjórr; m; bull; 1; –; –; (43495). Old Prussian; tauris; –; European bison, wisent; 3; –; –; (43490). Old Swedish; þjiūr; m; bull; 1; –; –; (43583). Oscan; taurz*; m; bull; 1; –; –; (43581). Polish; tur; m; aurochs; 3; –; –; (43481). Portuguese; touro; m; bull; 1; –; –; (54220). Proto-Albanian; *taura; –; bull; 0; –; –; (43494). Proto-Balto-Slavic; *taurós; –; –; 0; –; –; (43478). Proto-Celtic; *tarwo-; –; bull; 0; –; –; (43471). Proto-Germanic; *þeura-; m; bull; 0; –; –; (43474). Proto-Indo-European; *tawro-; –; –; 0; –; –; (43470). Proto-Indo-European; *teh₂u-ro-; –; bull; 0; –; –; (43476). Proto-Indo-European; *th₂euro-; –; –; 0; –; –; (43479). Proto-Italic; *tauro-; –; bull; 0; –; –; (43579). Proto-Slavic; *tȗrъ; m; aurochs; 0; –; –; (43477). Provençal; taur; m; bull; 1; –; –; (54229). Romanian; taur; m; bull; 1; –; –; (54223). Russian; tur; m; aurochs; buffalo; 3; –; –; (43482). Scottish Gaelic; tarbh; m; bull; 1; –; –; (43623). Serbian; tûr; m; aurochs; 3; –; –; (43485). Slovene; tȗr; m; aurochs, European bison; 3; –; –; (43483). Spanish; toro; m; bull; 1; –; –; (54217). Swedish; tjur; c; bull; 1; –; –; (43468). Umbrian; turs*; m; bull; 1; –; –; (43580). Welsh; tarw; m; bull; 1; –; –; (43619). PIE *steh₂w-ro- ‘big cattle’ (?) (54367) Avestan; staora-; m; big cattle; camel, horse, bovine and donkey; 3; –; –; (43491). Dutch; stier; c; bull; 1; –; –; (54379). English; steer; –; young male bovine, esp. castrated; male beef-cattle of any age; 3; –; –; (54384). English; stirk; –; yearling cow; young bullock or heifer; 3; –; –; (54388). German; Stier; m; bull; 1; –; –; (54368). Gothic; stiur; m; bull; 1; –; –; (54397). Middle Dutch; stier; m; bull, male bovine; 1; –; –; (54380). Middle English; steore, ster, steyr, steer; –; young bull or ox, especially castrated; 3; –; –; (54385). Middle High German; stier; m; bull; 1; –; –; (54369). Middle Low German; stêr; m; bull; 1; –; –; (54377). Old English; stēor; m; young bull or ox, especially castrated; 3; –; –; (54386).

452

Appendix 3b: Lexical data: Indo-European

Old English; stīrc, stȳrc, stȳric, stīorc; n; calf; young bullock; heifer; 3; –; –; (54389). Old High German; stior; m; bull; 1; –; –; (54370). Proto-Germanic; *steura-; m; bull; 0; –; –; (54371). Proto-Germanic; *steura-; m; bull; 0; –; –; (54378). Proto-Germanic; *stiurikaz; –; bullock; 0; –; –; (54390). Sanskrit; sthaurá-; n; strength, firmness; 0; –; –; (54401). PGm *bullan ‘bull’, PCelt *ballo- ‘penis’ < PIE *bhel- ‘to swell’ (54402) Classical Greek; φαλλός; m; penis; 0; –; –; (54483). Dutch; bul; c; bull; 1; –; –; (54421). English; bull; –; uncastrated male bovine; 1; –; –; (54428). English; bullock; –; castrated male of domestic cattle, raised for beef; 3; –; –; (54433). Faroese; boli; m; large animal; 0; –; –; (54410). Gaulish; Ballo-marios; –; –; 0; –; –; (54478). German; Bulle; f; bull (for breeding); male whale, male elephant; 1; –; –; (54414). Icelandic; boli; m; bull; 1; –; –; (54406). Irish; ball; m; limb, member; 0; –; –; (54464). Latin; follis; m; bag, sack; ball, testicle; 0; –; –; (54481). Latvian; bullis; m; ox; 4; Loan; Middle Low German; (54459). Middle Dutch; bul, bulle, bolle; m; bull; 1; –; –; (54422). Middle English; bole, boole; –; bull; 2; Loan; Old Norse; (54439). Middle English; bule, bulle; –; bull; 1; –; –; (54429). Middle English; bulluc, bullok, bolok, bullocke, bullock; –; young bull, bull calf; castrated bull, ox; 3; –; –; (54434). Middle Low German; bulle; m; bull; 1; –; –; (54415). Middle Welsh; balleg; –; sack, purse; 0; –; –; (54475). Old English; *bulla; m; bull; 1; –; –; (54430). Old English; bulluc; m; young bull, bull calf; 3; –; –; (54435). Old Irish; ball; m; member, penis; 0; –; –; (54465). Old Norse; boli, bole; m; bull, ox; 1; –; –; (54403). Proto-Celtic; *ballo-; –; member, penis; 0; –; –; (54466). Proto-Germanic; *bulan-, *bullan-; –; bull; 0; –; –; (54404). Proto-Indo-European; *bhel-, *bhel-; v; to blow, grow, swell; 0; –; –; (37039). Proto-Indo-European; *bhln-; –; –; 0; –; –; (54482). Scottish Gaelic; ball; m; limb, member, penis; 0; –; –; (54468). PGm *farza(n)- ‘young bull’ < PIE *prh₃-o‘providing’ (54485)

Catalan; parir; v; to give birth; 0; –; –; (54572). Dutch; vaar; adj; without calf; 0; –; –; (54535). Dutch; vaars; c; heifer; 3; –; –; (54530). Dutch; var; c; young bull; 3; –; –; (54525). English; farrow; adj; (of cow) without calf; 0; –; –; (54546). Frisian; fear; –; feather (not down); heifer; 0; –; –; (25956). German; Farre; m; young bull; 3; –; –; (54490). German; Färse; f; heifer, young cow; 3; –; –; (54496). Latin; parere; v; to give birth to, bear; 0; –; –; (54565). Middle Dutch; vare, varre; m; young bull; 3; –; –; (54526). Middle Dutch; verse, vaerse; f; heifer; 3; –; –; (54531). Middle English; farrow; adj; (of cow) without calf; 0; –; –; (54547). Middle High German; far, farre, var, varre; m; young bull; 3; –; –; (54491). Middle High German; verse; f; heifer; 3; –; –; (54497). Middle Low German; varre; m; bull, young bull; 1; –; –; (54514). Middle Low German; verse; f; heifer, young cow; 3; –; –; (54518). Middle Low German; vōr; –; piglet, young pig; skinny piglet; 0; –; –; (54522). Old English; fearr; m; bull; 1; –; –; (54553). Old Frisian; fēring; m; (young) bull; 1; –; –; (54560). Old High German; far, farro; m; bull, ox; 1; –; –; (54492). Portuguese; parir; v; to give birth (esp. of animals); 0; –; –; (54568). Proto-Germanic; *farsjō-; –; heifer; 0; –; –; (54498). Proto-Germanic; *farwa-, *farzwa-; adj; young bull; 0; –; –; (54488). Proto-Germanic; *farza-, *farzan-; m; young bull; 0; –; –; (54487). Proto-Germanic; *fōra-; m; piglet; 0; –; –; (54523). Proto-Indo-European; *pérh₃-i-; v; to provide; 0; –; –; (54567). Proto-Indo-European; *por-; v; to be with young; 0; –; –; (54489). Proto-Indo-European; *pórs-ieh₂-; –; –; 0; –; –; (54499). Proto-Italic; *per(e)i-, par-(e)i-; v; to bear; find, experience; 0; –; –; (54566). Spanish; parir; v; to give birth; 0; –; –; (54564). PIE *gʷh₃urs-en- ‘male bovine’ (54588) Dutch; kuis; c; calf; 3; –; –; (54603). Icelandic; kussi; m; bull calf; 3; –; –; (54596). Middle High German; kuose; f; female calf, sheep; 3; –; –; (54600). Old Norse; kussi; m; bull calf; 3; –; –; (54589). Proto-Germanic; *kursan-; m; bull calf; 0; –; –; (54590).

Appendix 3b: Lexical data: Indo-European

Proto-Indo-European; *gʷh₃urs-en-; –; –; 0; –; –; (54591). Proto-Indo-European; *gʷow-wṛsēn-; –; –; 0; –; –; (54607). Proto-Tocharian; *kæwurṣæ; –; –; 0; –; –; (54609). Sanskrit; go-vrṣá-; m; bull; 1; –; –; (54606). Swedish; kossa; c; cow; 3; –; –; (54592). Tocharian A; kayurṣ; m; bull, yak-bull; 1; –; –; (54608). Tocharian B; kauurṣe*; m; bull; 1; –; –; (54611). PT *sārm ‘seed’ (uct. etym.) (54614) Proto-Tocharian; *sārm; –; seed; 0; –; –; (54617). Proto-Tocharian; *sārm-én; –; bull; 0; –; –; (54616). Tocharian B; sārme; m; bull; 1; –; –; (54615). Skt sāṇḍa- ‘bull’ (uct. etym.) (54618) Bengali; ṣaṇḍa; –; bull; 1; –; –; (54623). Hindi; saṇḍā; adj,m; burly, fat; fat ox; 0; –; –; (54621). Hindi; shanḍ; m; bull, bullock; 1; –; –; (54620). Punjabi; sanḍhā, sáṇḍh; m; bull, stallion; barren (of women or animals); 1; –; –; (54624). Sanskrit; sāṇḍa-; adj; uncastrated (of bull); 0; –; –; (54619). IIr *ānd(r)á- ‘egg, testicle’ (54626) Bengali; ãṝ uā; –; bull-calf; 3; –; –; (54631). ̄ ū; –; uncastrated; 0; –; –; (54629). Hindi; ãḍ Proto-Indo-European; *ondó-; –; –; 0; –; –; (54628). Punjabi; āṇḍū; adj; uncastrated; 0; –; –; (54633). Sanskrit; āṇḍá-; –; egg; testicles; 0; –; –; (54627). PIE *porḱo- ‘young pig, piglet’ (59431) Old Norse; farri; m; ox, steer, bull; boar; 3; –; –; (54486). PIE *pōr-o- ‘young of animal’ < PIE *per- ‘to give birth’ (59843) Classical Greek; πόρτις, πόρις, -ιος; f; calf, heifer; (metaph.) young girl; 3; –; –; (54582). Modern Armenian; ort’; –; calf, fawn; 3; –; –; (54579). Proto-Indo-European; *por-i-; –; –; 0; –; –; (54580). Sanskrit; pṛthuka-; m; boy; young of any animal; calf; 3; –; –; (54585). No etym. (–) Danish; tyr; c; bull; 1; –; –; (43585). calf PIE *gʷelbh-u- ‘young animal, womb’ (55264) Avestan; garəβa-; m; womb; 0; –; –; (55269). Avestan; gərəbuš-; n; young animal; 3; –; –; (55267). Classical Greek; δελφύς; f; womb; 0; –; –; (55265). Danish; kalv; c; calf; 1; –; –; (55283). Dutch; kalf; n; calf; 1; –; –; (55313). Elfdalian; kåv; m; calf; 1; –; –; (55298). English; calf; –; the young of the cow; also the young of other animals, such as elephants, deer, whales; 1; –; –; (55320).

453

Faroese; kálvur; m; calf; 1; –; –; (55295). German; Kalb; n; calf; 1; –; –; (55301). Gothic; kalbo; f; calf; 1; –; –; (55332). Icelandic; kálfur; m; calf; 1; –; –; (55292). Middle Dutch; kalf; n; calf; 1; –; –; (55314). Middle English; calf; –; calf; 1; –; –; (55321). Middle High German; kalp; n; calf; 1; –; –; (55302). Norwegian (Bokmål); kalv; m; calf; 1; –; –; (55286). Norwegian (Nynorsk); kalv; m; calf; 1; –; –; (55289). Old English; cealf, calfur; n; calf; 1; –; –; (55322). Old English; cilfor-lamb; f; female lamb; 0; –; –; (55329). Old High German; chalp, kalp; n; calf; 1; –; –; (55303). Old High German; kalba; f; female calf; 1; –; –; (55310). Old Norse; kalfr; m; calf; 1; –; –; (55274). Old Saxon; kalf; n; calf; 1; –; –; (55318). Old Swedish; kalver; m; calf; 1; –; –; (55276). Proto-Germanic; *kalbiz-; n; calf; 0; –; –; (55275). Proto-Germanic; *kalbōn-; –; female calf; 0; –; –; (55311). Proto-Germanic; *kelbuza-; –; –; 0; –; –; (55330). Proto-Indo-European; *gʷelbhu-; –; womb; 0; –; –; (55266). Sanskrit; gárbha-; m; womb; 0; –; –; (55271). Swedish; kalv; c; calf; 1; –; –; (55279). OIr gamuin ‘calf’ (no etym.) (55335) Irish; gamhain; m; calf; 1; –; –; (55336). Old Irish; gamuin, gamain; m; calf; 1; –; –; (55337). Scottish Gaelic; gamhainn; m; steer, young bullock; young bull; heifer; yearling deer; 3; –; –; (55338). PIE *leh₂p- ‘cattle’ (55341) Albanian (Tosk); lopë; f; cow; 3; –; –; (55382). Breton; leue; m; calf; 1; –; –; (55368). Cornish; lugh; m; calf; 1; –; –; (55375). Irish; lao; m; young calf; 1; –; –; (55345). Latvian; lops, lùops; m; farm animal; 1; –; –; (55342). Lithuanian; lúopas, lúobas; m,f; clumsy person or animal; 1; –; –; (55343). Middle Breton; lue; –; calf; 1; –; –; (55369). Middle Welsh; lloe, llo; m; calf; 1; –; –; (55357). Old Cornish; loch; –; calf; 1; –; –; (55376). Old Irish; lóeg; m; calf; 1; –; –; (55346). Old Welsh; lo; m; calf; 1; –; –; (55358). Proto-Albanian; *lāpā; –; –; 0; –; –; (55383). Proto-Celtic; *lāfigo-; –; calf; 0; –; –; (55347). Proto-Indo-European; *leh₂p-; –; cattle; 0; –; –; (55348). Scottish Gaelic; laogh; m; calf; the young of a cow or deer; 1; –; –; (55349). Welsh; llo; m; calf; 1; –; –; (55356). Lat novus ‘new’ (55385) Latin; novus; –; new; 0; –; –; (33652).

454

Appendix 3b: Lexical data: Indo-European

Portuguese; novilho; m; young bull, young ox; 2; Loan; Spanish; (55390). Spanish; novilla; f; young heifer; 1; –; –; (55386). Spanish; novillo; m; young bull; 3; –; –; (55387). Spanish; nuevo; –; new; 0; –; –; (33091). Lat terner ‘young, tender’ (55394) Latin; terner; adj; young, tender; 0; –; –; (55397). Portuguese; tenro; adj; tender; 0; –; –; (55399). Portuguese; terneiro, terneira; m,f; calf; 1; –; –; (55398). Spanish; ternero, ternera; m,f; calf; 1; –; –; (55395). Spanish; tierno; adj; tender; 0; –; –; (55396). PIE *mogh-u- ‘young person’ (55401) Albanian (Tosk); meksh; m; bison calf; 3; –; –; (55414). Albanian (Tosk); meksh; m; bull-calf; 3; –; –; (55411). Avestan; maγava-; –; unmarried; 0; –; –; (55417). Gothic; magus; –; boy; 0; –; –; (55402). Gothic; mawi; –; young girl; 0; –; –; (55405). Old Irish; mug; m; slave; 0; –; –; (55408). Proto-Albanian; *maguša; –; –; 0; –; –; (55412). Proto-Celtic; *mogu-; –; servant; 0; –; –; (55403). Proto-Indo-European; *magh-u-, *maghu-, *maghos; –; –; 0; –; –; (37726). Proto-Indo-European; *mogh-u-; –; young person; 0; –; –; (55404). PIE *bheh₁i-tu- ‘fetus, offspring (?)’ (55419) Proto-Indo-European; *bheh₁i-t-u-; –; fetus, offspring (?); 0; –; –; (55421). Tocharian B; paitar*; –; calf; 1; –; –; (55420). Skt vatsá- ‘calf’ < PIE *wet- ‘year’ (55422) Bengali; bāchā; –; calf, young of animal, dear child; 1; –; –; (55425). Hindi; bacherā; m; colt, calf; 3; –; –; (55424). Punjabi; vacchā; m; calf; 1; –; –; (55426). Sanskrit; vatsá-; m; calf; calf; yearling; yearling, calf, child; 1; –; –; (55423). No etym. (–) Ossetian (Iron); rod; –; calf; 1; –; –; (94240). cat Gr αἰόλος + οὐρά ‘with moving tail’ (61289) Classical Greek; αἴλουρος, αἰέλουρος; m,f; cat; weasel; 1; –; –; (61290). Proto-form *gat- ‘cat’ (migr.) (61291) Breton; kazh; m; cat; 1; –; –; (61435). Catalan; gat, gata; m,f; cat; 1; –; –; (61304). Classical Greek; κάττα, κάττος; f,m; cat; 2; Loan; Latin; (61313). Cornish; kat, kath; f; cat; 1; –; –; (61440). Czech; kočka; f; cat; 1; –; –; (61315). Danish; kat; c; cat; 1; –; –; (61347). Dutch; kat; c; cat; 1; –; –; (61399). Elfdalian; katt; m; cat; 1; –; –; (61383). English; cat; –; (domesticated) small mammal of the species Felis catus; 1; –; –; (61406). Faroese; ketta; f; (female) cat; 1; –; –; (61378). Faroese; køttur, kattar; m; cat; 1; –; –; (61374). French; chat, chatte; m; cat; 1; –; –; (61298).

Gaulish; Cattos; –; cat (personal name); 1; –; –; (61442). German; Katze; f; cat; 1; –; –; (61387). Icelandic; köttur; m; cat; 1; –; –; (61370). Irish; cat; m; cat; 1; –; –; (61422). Italian; gatto, gatta; m,f; cat; 1; –; –; (61292). Latin; cattus; m; cat (wild, later domesticated); 2; Loan; Afro-Asiatic (family); (61293). Lithuanian; katė; f; cat; 1; –; –; (61328). Middle Breton; caz; –; cat; 1; –; –; (61436). Middle Dutch; catte, kat; f; cat; 1; –; –; (61400). Middle English; cat; –; cat; 1; –; –; (61407). Middle High German; katze; f; cat; 1; –; –; (61388). Middle Low German; katte; f; cat; 1; –; –; (61396). Middle Welsh; cath; m,f; cat; 1; –; –; (61433). Modern Armenian; katu; –; cat; 1; –; –; (61309). Modern Greek; γἀτα; f; cat; 2; Loan; Italian; (61310). Norwegian (Bokmål); katte; m,f; cat; 1; –; –; (61351). Norwegian (Bokmål); kjette; m,f; female cat; 1; –; –; (61355). Norwegian (Nynorsk); katte; f; cat; 1; –; –; (61360). Norwegian (Nynorsk); kjette; f; female cat; 1; –; –; (61365). Occitan; gat, gata; m,f; cat; 1; –; –; (61296). Old English; catte, catt; m; cat; 1; –; –; (61408). Old Frisian; katte; f; cat; 1; –; –; (61418). Old High German; kazza; f; cat; 1; –; –; (61389). Old Irish; catt; m; cat; 1; –; –; (61423). Old Norse; ketta; f; (female) cat; 1; –; –; (61334). Old Norse; kǫttr; m; cat; 1; –; –; (61330). Old Russian; kotьka; f; cat; 1; –; –; (61325). Old Swedish; katter; m; cat; 1; –; –; (61338). Polish; kot; m; cat (generic)); male cat; 1; –; –; (61319). Polish; kotka; f; female cat; 1; –; –; (61318). Portuguese; gato, gata; m,f; cat; 1; –; –; (61302). Proto-Celtic; *katto-; –; cat; 0; Loan; Latin; (61424). Proto-Germanic; *kattjōn-; –; female cat; 0; –; –; (61335). Proto-Germanic; *kattōn-; f; cat; 0; Loan; Latin; (61332). Proto-Germanic; *kattu-; –; cat; 0; –; –; (61331). Proto-Slavic; *kotъ; –; cat; 0; Loan; Latin; (61316). Provençal; gat; m; cat; 1; –; –; (61306). Russian; koška; f; cat; 1; –; –; (61322). Sardinian; battu; m,f; cat; 1; –; –; (61294). Scottish Gaelic; cat; m; cat; 1; –; –; (61425). Spanish; gato; m; cat; 1; –; –; (61300). Swedish; katt; c; cat; 1; –; –; (61342). Welsh; cath; f; cat; 1; –; –; (61431). Lat fēles ‘cat’ (61444) Latin; fēles; f; cat; 1; –; –; (61446). Welsh; beleu; –; marten; 0; –; –; (61445). Proto-form *pis-, *pus- ‘cat’ (symb.) (61447) Romanian; pis; –; a call-word for cats; 0; –; –; (61449). Romanian; pisică; f; cat; 1; –; –; (61448).

Appendix 3b: Lexical data: Indo-European

CoSl mačka ‘cat’ (61450) Albanian (Tosk); mac̷e; f; cat; 2; Loan; SerboCroatian; (61451). Croatian; máčak; m; male cat; 1; –; –; (61460). Croatian; mȁčka; f; cat; 1; –; –; (61459). Czech; macek; m; male cat; 3; –; –; (61454). Czech; macka; f; cat; 3; –; –; (61453). Serbian; máčak; m; male cat; 1; –; –; (61463). Serbian; mȁčka; f; cat; 1; –; –; (61462). Serbo-Croatian; mȁčka; f; cat; 1; –; –; (61452). Slovene; máček; m; male cat; 1; –; –; (61457). Slovene; mȃčka; f; cat; 1; –; –; (61456). Latv kaķis (uct. etym.) (61465) Latvian; kaķis, kaķe; m,f; cat; 1; –; –; (61466). Skt bíḍāla- < *vi-dāla- ‘animal that attacks and tears’ (61467) Bengali; birāl, bilāl, bilāi; –; cat; 1; –; –; (61470). Hindi; bilāṛ; m; cat; 1; –; –; (61469). Punjabi; bilī; f; cat; 1; –; –; (61471). Sanskrit; bíḍāla-; m; cat; 1; –; –; (61468). Skt mārjara- ‘cat’ < Skt mṛj- ‘to wipe, to clean’ (61472) Hindi; mãjār; m; cat; 1; –; –; (61475). Punjabi; mãj̄ ār; m; cat; 1; –; –; (61476). Sanskrit; mārjāra-; m; cat; 1; –; –; (61473). Sanskrit; mṛj-; v; to wipe, to clean; 0; –; –; (61474). Tocharian B; mārjāre*; –; cat; 2; Loan; Sanskrit; (61477). cattle (coll.) PIE *gʷeh₃-u- ‘cow’ (54635) Bengali; goru, garu; –; any animal of the bovine species, cattle; stupid person; 3; –; –; (55435). Hindi; gorū; m; ox; 3; –; –; (55431). Proto-Indo-European; *gʷeh₃-u-; –; cow; 0; –; –; (54638). Proto-Indo-European; *gʷou-; –; cow; 0; –; –; (54796). Punjabi; gorū; m; cattle (excluding buffalos); 1; –; –; (55439). Sanskrit; gōrūpá-; –; cow-shaped; 0; –; –; (55428). < PIE *ḱr- ‘horn’ (55443) Dutch; rund; n; cow, bovine (generic); 3; –; –; (55462). German; Rind; n; cow (generic bovine); beef; (plural) cattle; 3; –; –; (55447). Icelandic; hrútur; m; ram; the constellation Aries; 0; –; –; (55445). Middle Dutch; rent, rint, rynt; n; cattle; 1; –; –; (55463). Middle English; rotheren; adj; of oxen or cattle; 0; –; –; (55476). Middle English; ryther, ruther, rother; –; a horned bovine animal, esp. (in later use) an ox, a bullock; 3; –; –; (55472). Middle High German; rint; n; cow (generic bovine); beef; (plural) cattle; 3; –; –; (26163).

455

Middle Low German; rint, runt, ront; n; bovine animal (generic); young ox, heifer; 3; –; –; (55459). Old English; hrīþer, hrīðer, hryþer, hruðer; n; cow, bovine; 3; –; –; (55473). Old English; hriþeru; n; cattle; 1; –; –; (55477). Old Frisian; hrīther, rīther, rēther, rēder, rēr; n; bovine animal; 3; –; –; (55483). Old High German; hrind, hrint, rint; n; cow, bovine; 3; –; –; (55449). Old Norse; hrútr; m; wether, castrated ram; 0; –; –; (55444). Old Saxon; hrīth; n; bovine animal; 3; –; –; (55469). Proto-Germanic; *hrinþiz-, *hrinþez-, *hrunþiz-; n; cow, bovine; cattle; 0; –; –; (55450). Proto-Indo-European; *ḱer-; v; to grow; 0; –; –; (30915). Proto-Indo-European; *ḱr-ént-es-; –; –; 0; –; –; (55451). PIE *bhorw-o- < *bher- ‘to carry’ (55486) Albanian (Tosk); bravë; f; herd; 4; Loan; ProtoSlavic; (55531). Czech; brav; m; small live stock; hog, castrated boar; 3; –; –; (55536). Dutch; barg; c; castrated boar; 0; –; –; (55509). English; barrow; –; castrated boar; 0; –; –; (55516). Frisian; baerg; –; castrated boar; 0; –; –; (55528). Middle Dutch; barg, barch; m; castrated boar; 0; –; –; (55510). Middle English; baru, barrow; –; castrated boar; 0; –; –; (55517). Middle High German; barc; m; castrated boar; 0; –; –; (55502). Norwegian (Bokmål); barre; –; ram; 0; –; –; (55494). Norwegian (Nynorsk); barre; –; ram; 0; –; –; (55498). Old English; bearg, bearh; m; castrated boar; 0; –; –; (55518). Old High German; barug, barh; m; castrated boar; 0; –; –; (55503). Old Norse; borgr; m; castrated boar; 0; –; –; (55487). Polish; browek; –; porker; young fattened pig; 0; –; –; (55542). Proto-Albanian; *barwa; –; –; 0; –; –; (55535). Proto-Germanic; *baruga-; m; castrated boar; 0; –; –; (55488). Proto-Indo-European; *bhor-u-o-; –; –; 0; –; –; (55538). Proto-Slavic; *bȏrvъ; m; –; 0; –; –; (55532). Russian; bórov; m; hog, castrated boar; 0; –; –; (55545). Slovene; brȃv; m,f; pig; sheep (coll.); animal; sheep (coll.); 0; –; –; (55548). Swedish; barre; –; ram; 0; –; –; (55490). Arm ar, duar ‘cattle’ < PIE *dṓm- ‘house’ (55554) Avestan; dam-; –; house; 0; –; –; (55563). Classical Greek; δῶ; n; house; 0; –; –; (55559).

456

Appendix 3b: Lexical data: Indo-European

Latin; domus; f; house, household; 0; –; –; (55555). Modern Armenian; tuar, duar; –; cattle; 1; –; –; (55557). Old Church Slavonic; domъ; m; house; 0; –; –; (55561). Proto-Indo-European; *dṓm-; –; house; 0; –; –; (55556). Sanskrit; dám-; –; house; 0; –; –; (55565). PIE *meh₁lo- ‘small cattle’ (55567) Classical Armenian; mal; –; property, possession; cattle; 4; –; –; (55569). Classical Greek; μῆλον; n; small cattle, sheep and goats; 3; –; –; (88497). Cornish; mil; m; animal; 0; –; –; (56046). Dutch; maal; c; young cow; 3; –; –; (56022). Irish; míol; m; animal, insect, louse, creature; 0; –; –; (32535). Middle Breton; mil; m; animal; 0; –; –; (56043). Middle Welsh; mil; m; animal; 0; –; –; (56037). Modern Armenian; mal; –; bullock, cattle; 3; –; –; (55568). Old Church Slavonic; malъ; adj; small; 0; –; –; (56058). Old Cornish; mil; –; animal; 0; –; –; (56047). Old Irish; mil; n; small animal; 0; –; –; (56026). Proto-Celtic; *mīlo-; –; animal; 0; –; –; (56027). Proto-Germanic; *mēlō-; –; young animal; 0; –; –; (56023). Proto-Indo-European; *meh₁lo-; –; small animal, small cattle; 0; –; –; (56024). Proto-Slavic; *malъ; –; –; 0; –; –; (56056). Russian; malíč; –; breed of sheep; 0; –; –; (56055). Scottish Gaelic; mial, mialiach, míol; f; animal, insect, creature, louse; 0; –; –; (32590). Welsh; milyn; m; animal, beast, creature; animal not usually consumed by man; 0; –; –; (56036). PGm *nauta, PSl *nuta < PIE *neud- ‘to acquire’ (55573) Dutch; noot; –; cattle, bovine; 1; –; –; (55655). Elfdalian; nǫt; n; night; bovine, beast; cattle; 0; –; –; (31816). English; neat; –; (collective) cattle; 1; –; –; (55668). Faroese; neyt; n; ox, beast; (coll.) cattle; fool; 3; –; –; (55621). Frisian; nut, nuat, nuet, nyt, nüjtt; –; animal; 0; –; –; (55683). German; Noß; n; cattle (dialect); 1; –; –; (55631). Gothic; niutan; –; to enjoy, make use of; 0; –; –; (55692). Icelandic; naut; n; beast, bovine; 0; –; –; (55616). Latvian; nauda; f; property, money, fee; 3; –; –; (55584). Lithuanian; naudà; –; use, profit, property; 0; –; –; (55587). Middle Dutch; noot; n; bovine animal, especially for meat; 3; –; –; (55656).

Middle English; naut, nout, nēat, nete; –; bovine animal: ox, bullock, cow, heifer; (collective) cattle; 3; –; –; (55669). Middle High German; nōz; n; cattle, livestock; 1; –; –; (55632). Middle Low German; nōt-; –; bovine, cattle; 3; –; –; (55651). Norwegian (Bokmål); naut; n; beast, bovine; cow, bull or calf; (coll.) cattle; fool; 0; –; –; (55606). Norwegian (Nynorsk); naut; n; beast, bovine; cow, bull or calf; (coll.) cattle; fool; 0; –; –; (55611). Old Church Slavonic; nuta; f; cow, ox, cattle; 3; –; –; (55579). Old English; nēat; n; a bovine animal: ox, bullock, cow, heifer; 3; –; –; (55670). Old Frisian; nāt; –; animal; 0; –; –; (55684). Old High German; nōz; n; cattle, livestock; 1; –; –; (55633). Old Norse; naut; n; beast, bovine; 0; –; –; (55591). Old Saxon; nōt, nōtil; m; domestic animal; 3; –; –; (55664). Old Swedish; nöt; n; beast, bovine; 0; –; –; (55595). Proto-Balto-Slavic; *naudā-; –; –; 0; –; –; (55585). Proto-Germanic; *nauta-; –; utilizable cattle; 0; –; –; (55576). Proto-Germanic; *neutan-; v; to make use of, enjoy; 0; –; –; (55577). Proto-Indo-European; *néud-e-; –; –; 0; –; –; (55578). Proto-Indo-European; *newd-, *nowd-; v; to seize, to take for use; 0; –; –; (55586). Proto-Slavic; *nuta; f; cattle; 0; Loan; ProtoGermanic; (55575). Slovene; núta; f; herd of cattle; 3; –; –; (55574). Swedish; nöt; n; beast, bovine; 0; –; –; (55600). Swiss German; Nooss; –; young sheep or goat; 0; –; –; (55646). PIE *peḱ-u- ‘cattle’ (55696) Avestan; pasu-; m; cattle; domestic animal, sheep; 1; –; –; (55780). Classical Armenian; asr; –; fleece, wool; 0; –; –; (55769). Classical Greek; πέκω; v; to comb (oneself), to card, to shear; to comb, to card, to shear; 0; –; –; (55771). Classical Greek; πόκος; m; wool of sheep, fleece; fleece; wool that has been plucked or shorn from the sheep; 0; –; –; (55773). Danish; fæ; n; cattle, beast; domestic animal; 1; –; –; (55709). Dutch; vee; n; cattle; 1; –; –; (55744). English; fee; –; money paid in exchange for service, etc; 0; –; –; (55754). Faroese; fæ; n; cattle; 1; –; –; (55725). German; Vieh; n; livestock; cattle; 3; –; –; (55729).

Appendix 3b: Lexical data: Indo-European

Gothic; faihu; n; movable goods, possessions, cattle, money; 3; –; –; (55766). Hindi; pas; f; buffalo-heifer; 3; –; –; (55789). Hindi; pasū; m; animal (such as goat or sheep); 0; –; –; (55787). Icelandic; fe; n; livestock, money, property; 3; –; –; (55721). Lithuanian; pẽkus; m; cattle, small livestock; 1; –; –; (55776). Middle Dutch; vee, ve, veeh, vieh, vie, veede; n; cattle; 1; –; –; (55745). Middle English; fee; –; livestock, cattle large or small; moveable property; money; 3; –; –; (55755). Middle High German; vihe, vehe, vëhe, vih, vie, vê; n; cattle; 1; –; –; (55730). Middle Low German; vê, vie, vi; n; cattle; 1; –; –; (55741). Norwegian (Bokmål); fe; n; livestock; 3; –; –; (55713). Norwegian (Nynorsk); fe; n; livestock; 3; –; –; (55717). Old English; feoh, fioh; n; cattle, property, money; 1; –; –; (55756). Old High German; fihu; n; cattle, animal, money; 1; –; –; (55731). Old Norse; fé, fjár; n; beast (sing.); cattle, livestock (pl.); property, money; 0; –; –; (55697). Old Prussian; pecku; n; livestock, cattle; 3; –; –; (55778). Old Saxon; fehu, fihu, fê; n; cattle; property; 1; –; –; (55751). Old Swedish; fǣ; n; beast, livestock; property; 0; –; –; (55700). Proto-Balto-Slavic; *peku; –; –; 0; –; –; (55777). Proto-Germanic; *fehu-; n; cattle; 0; –; –; (55698). Proto-Indo-European; *peḱ-e/o-, *peḱ-e/o; –; –; 0; –; –; (55772). Proto-Indo-European; *peḱ-u-; n; cattle; livestock; 0; –; –; (55740). Sanskrit; páśu-, paśú-; m,n; cattle, animal; domestic or sacrificial animal; goat; 1; –; –; (55782). Swedish; fä; n; beast, domestic animal; 0; –; –; (55704). PGm *skatta- ‘wealth, property, cattle’ (55790) Bulgarian; skot; m; cattle; 1; –; –; (55860). Croatian; skȍt; m; brood, animal’s young; female animal which has given birth, animal; 3; –; –; (55854). Czech; skot; m; cattle, livestock; 1; –; –; (55842). Danish; skat; c; tax, treasure; 0; –; –; (55800). Dutch; schat; c; treasure, wealth; 0; –; –; (55829). Elfdalian; skatt; m; tax, treasure; 0; –; –; (55815). Faroese; skattur; m; tax, treasure; 0; –; –; (55812). German; Schatz; m; treasure; wealth; 0; –; –; (55818). Gothic; skatts; m; coin; 0; –; –; (55840). Icelandic; skattur; m; tax; 0; –; –; (55809).

457

Middle Dutch; skat, scat, schat; m; money, wealth, treasure; 0; –; –; (55830). Middle High German; schaz, schatz; m; money and goods, wealth, treasure, fortune; 3; –; –; (55819). Middle Low German; schat; m; treasure, wealth; tax; 0; –; –; (55827). Norwegian (Bokmål); skatt; m; tax, treasure; 0; –; –; (55803). Norwegian (Nynorsk); skatt; m; tax, treasure; 0; –; –; (55806). Old Church Slavonic; skotъ; m; cattle; 1; –; –; (55863). Old English; sceat; m; property, goods, wealth; 3; –; –; (55836). Old Frisian; sket; m,n; goods, property, cattle; 3; –; –; (55838). Old High German; scaz, skaz; m; treasure, money, wealth, tax; 0; –; –; (55820). Old Norse; skattr; m; tribute, tax; treasure; 0; –; –; (43769). Old Saxon; skat; m; treasure, money, possession; 0; –; –; (55834). Old Swedish; skatter; m; tax, treasure; 0; –; –; (55793). Polish; skot; m; cattle; 1; –; –; (55845). Proto-Germanic; *skatta-; m; wealth, property, cattle; 0; –; –; (43768). Proto-Slavic; *skotъ; m; cattle; 0; Loan; ProtoGermanic; (55843). Russian; skot; m; cattle, livestock; 1; –; –; (55848). Serbian; skȍt; m; brood, animal’s young; female animal which has given birth; 3; –; –; (55857). Slovene; skòt; m; brood, animal’s young; 3; –; –; (55851). Swedish; skatt; c; tax, treasure; 0; –; –; (55796). PIE *gʷh₃ig(w)o- ‘alive’ (55866) English; quick; adj; taking only a short time, fast; (obsolete) alive; 0; –; –; (55886). Gothic; qius; adj; alive; 0; –; –; (55901). Latin; vīvus; adj; alive, living; 0; –; –; (55904). Lithuanian; gývas; adj; living, alive; 0; –; –; (55905). Middle Dutch; quic, quec; adj,n,m; alive; living animal; young animal; 0; –; –; (55880). Middle English; quek, queke, quike, quick; adj,n,m; alive; living, alive; animate; (of animals, esp. cattle) owned as livestock; (of property or wealth) consisting of live animals; 0; –; –; (55887). Middle High German; quëc, këc; adj,n; alive; living animal; 0; –; –; (55870). Middle Low German; quek, quik; n; cattle; 1; –; –; (55877). Old English; cwic, cwicu, cucu; adj; alive; 0; –; –; (55888). Old Frisian; kuic, quik, quek; adj; alive; 0; –; –; (55898).

458

Appendix 3b: Lexical data: Indo-European

Old High German; queh, quek, quec; adj; alive; 0; –; –; (55871). Old Norse; kvikr, kykr; adj; alive; 0; –; –; (55867). Old Saxon; quik; –; alive; 0; –; –; (55883). Proto-Germanic; *kʷik(w)o-; –; alive; 0; –; –; (55868). Proto-Indo-European; *gʷh₃ig(w)o-; –; –; 0; –; –; (55869). Sanskrit; jīvá-; –; alive, living; 0; –; –; (55906). ClArm arǰaṙ ‘any bovine animal’ (uct. etym.) (55907) Modern Armenian; arǰaṙ; –; any bovine animal; 3; –; –; (55908). < PIE *weyh1- ‘to follow’ (55909) Catalan; guanyar; v; to gain, to profit; 0; –; –; (56005). Faroese; veiða; v; to hunt; 0; –; –; (55941). French; gagnage; m; pasture; 0; –; –; (55981). French; gagner; v; to gain, to win, to profit; to plow (dial.); 0; –; –; (55975). Friulian; uadaña; –; ?; 0; –; –; (56013). German; Weide; f; pasture, meadow; grazing; 0; –; –; (55945). Gothic; *ganan; v; to covet; 0; –; –; (55965). Icelandic; veiða; v; to hunt; 0; –; –; (55937). Italian; guadagnare; v; to gain, to profit; 0; –; –; (55967). Late Latin; ganatus; –; ?; 0; Loan; Old Franconian; (55968). Middle English; gainage; –; profit or produce from the tillage of land; husbandry; 4; Loan; Old French; (55959). Middle English; waith; –; hunting, fishing; the unlawful taking of game; the right to take game; game, spoils; 0; Loan; Old Norse; (55956). Middle French; gaigner, gagner; v; to exploit, to benefit from, to cultivate, to plow; 0; –; –; (55976). Middle High German; weide, weid; f; feed, food, pasture; 0; –; –; (55946). Middle Low German; weiden; v; to hunt with falcons; 0; –; –; (55954). Norwegian (Bokmål); veida; v; to hunt; 0; –; –; (55928). Norwegian (Bokmål); veide; n; hunt, chase; 0; –; –; (55932). Norwegian (Nynorsk); veida; v; to hunt; 0; –; –; (55933). Occitan; guadanhar; v; to gain, to profit; 0; –; –; (55971). Old Danish; vede; v; to hunt; 0; –; –; (55925). Old English; wáð; f; hunting, wandering; 0; –; –; (55961). Old English; wæðan; v; to wander, to hunt; 0; –; –; (55963). Old Franconian; *waidanjan; –; autumn; 0; –; –; (55969). Old French; gaagnier; v; to exploit, to benefit from, to cultivate, to plow; 0; –; –; (55977).

Old French; guaaignage; m; ‘produce of the land, profit; arable land; pasture’; 3; –; –; (55960). Old French; guaainage; m; produce of the land, profit; arable land; pasture; 3; –; –; (55982). Old High German; weida; f; fodder, pasture, hunting, fishing; wandering, roaming; 0; –; –; (55947). Old Norse; veiða; v; to hunt, to capture; 0; –; –; (55912). Old Norse; veiðr; f; hunt; 0; –; –; (55910). Old Swedish; vēþa; v; to hunt; 0; –; –; (55915). Portuguese; gado; m; livestock, cattle; 3; –; –; (56001). Proto-Germanic; *waidanjan; –; –; 0; –; –; (55917). Provençal; guadanhar, gazanhar; –; ?; 0; –; –; (56009). Spanish; ganado; m; cattle, livestock; herd; crowd of people; 1; –; –; (55996). Spanish; ganar; v; to gain; 0; –; –; (55997). Swedish; veda; v; to hunt; 0; –; –; (55918). Swedish; vejda; v; to raise an obstacle against; 0; –; –; (55922). PAlb *sada, *seda ‘cattle’ < PIE *sed- ‘to walk’ (56017) Albanian (Tosk); gjedh; m; cattle; 1; –; –; (56018). Proto-Albanian; *sada, *seda; –; –; 0; –; –; (56019). PSl bȏgъ ‘god’ (56061) Albanian (Tosk); bagëti; fpl; herd, flock, sheep; 4; Loan; Proto-Slavic; (56062). Bulgarian; bogát; adj; rich; 0; –; –; (56083). Croatian; bògat; adj; rich; 0; –; –; (56077). Czech; bohatý; adj; rich; 0; –; –; (56065). Old Church Slavonic; bogatъ; adj; rich; 0; –; –; (56086). Polish; bogaty; adj; rich; 0; –; –; (56068). Proto-Slavic; *bogàtъ; adj; rich; 0; –; –; (56063). Proto-Slavic; *bȏgъ; m; god; 0; –; –; (56064). Russian; bogátyj; adj; rich; 0; –; –; (56071). Serbian; bògat; adj; rich; 0; –; –; (56080). Slovene; bogàt; adj; rich; 0; –; –; (56074). < PIE *sup-lo (?) (56089) Hittite; šupp(a)l(a)-; n; cattle; 1; –; –; (56090). Proto-Indo-European; *sup-lo-?; –; –; 0; –; –; (56091). Alb berr ‘sheep, goat’ (58160) Albanian (Tosk); berr; m; sheep, goat; wether, ram; livestock; 0; –; –; (55534). chicken Proto-form *glH-o-, *galn-o- ‘rooster’ (symb.) (59875) Latin; gallīna; f; hen; chicken (generic); 3; –; –; (59877). Latin; gallus; m; cock, rooster; 3; –; –; (59878). Portuguese; galinha; f; hen; chicken (generic); 3; –; –; (59888). Portuguese; galo; m; cock, rooster; chicken (generic); 3; –; –; (60239). Romanian; găină; f; hen; chicken (generic); 3; –; –; (59891).

Appendix 3b: Lexical data: Indo-European

Spanish; gallina; f; hen; chicken (generic); 3; –; –; (59885). Spanish; gallo; m; cock, rooster; 3; –; –; (60231). PCelt *kerkā ‘hen’ (symb.) (59902) Irish; cearc; f; hen; chicken (generic); 3; –; –; (59903). Irish; circeoil, circfheoil; f; chicken (meat); 3; –; –; (60541). Irish; circín; m; a little hen, a pullet; 3; –; –; (60537). Old Irish; cerc; f; hen; chicken (generic); 3; –; –; (59904). Proto-Celtic; *kerkā-; –; hen; 0; –; –; (59905). Scottish Gaelic; cearc; f; hen; chicken (generic); 3; –; –; (59906). PSl *kurica ‘hen’ (symb.?) (59924) Czech; kuře; f,n; chicken (generic and specific); 1; –; –; (60595). Polish; kura; f; hen; chicken (generic); 3; –; –; (60596). Russian; kúra; f; chicken (generic); hen; 1; –; –; (60597). PGm *hanan- ‘rooster’ < PIE *kan-on- ‘singer’ (59934) Danish; høns; npl; poultry; 3; –; –; (60452). Dutch; hoen; n; fowl, hen, chicken (generic); 3; –; –; (60487). Elfdalian; yöns; fpl; hens (coll.); 3; –; –; (60464). Faroese; høsn; npl; poultry, hens; 3; –; –; (60460). German; Huhn; n; hen; 3; –; –; (60468). Icelandic; hænsni; n; poultry; 3; –; –; (60456). Middle Dutch; hoen; n; hen (generic); 3; –; –; (60488). Middle High German; huon; n; hen; 3; –; –; (60469). Middle Low German; hôn; n; hen, chicken (generic); 3; –; –; (60483). Old High German; huon; n; hen; 3; –; –; (60470). Old Norse; hœns, hœnsn, hœnsni; npl; poultry; chickens (generic); 3; –; –; (60440). Old Saxon; hōn; n; hen, chicken (generic); 3; –; –; (60496). Old Swedish; höns; n; poultry; chicken (generic); 3; –; –; (60443). Proto-Germanic; *hanan-; m; cock, rooster; singer; 0; –; –; (59937). Proto-Germanic; *hōniz-; n; hen, fowl; 0; –; –; (60471). Swedish; höns; n; poultry; 3; –; –; (60447). PIE *h₂eu-i- ‘bird’ (60054) Latvian; vista; f; hen; chicken (generic); 3; –; –; (60066). Lithuanian; vištà; f; hen; chicken (generic); 3; –; –; (60067). Lat cāpus ‘capon, castrated cock’ (uct. etym.) (60289) Czech; slepice; f; hen; chicken (generic); 3; –; –; (60592). Czech; slepý; adj; blind; 3; –; –; (60593).

459

PGm *fugla- ‘bird’ < PIE *plewk- ‘float, fly’ (60380) Danish; fugl; c; bird; 3; –; –; (25547). Dutch; vogel; c; bird; 3; –; –; (25867). Elfdalian; fugel; m; bird; 3; –; –; (25721). English; fowl; –; chicken (generic), domestic cock or hen, of the species Gallus gallus; (in collective) any farm bird; 3; –; –; (60426). Faroese; fuglur; m; bird; 3; –; –; (25686). German; Vogel; m; bird; 3; –; –; (25756). Gothic; fugls; m; bird; 3; –; –; (26374). Icelandic; fugl; m; bird; 3; –; –; (25648). Middle Dutch; vogel, vuegel; m; bird; 3; –; –; (26307). Middle English; fowl; –; bird; 3; –; –; (60427). Middle High German; vogel; m; bird; 3; –; –; (26169). Middle Low German; vogel; m; bird; 3; –; –; (60417). Norwegian (Bokmål); fugl; m; bird; 3; –; –; (25579). Norwegian (Nynorsk); fugl; m; bird; 3; –; –; (25612). Old English; fugel, fugol, fugul; sm; bird; 3; –; –; (26090). Old Frisian; fugel, vugel; m; bird; 3; –; –; (26204). Old High German; fogal, fugal; m; bird; 3; –; –; (60410). Old Norse; fugl, fogl; m; bird; 3; –; –; (26006). Old Saxon; fugal, fugol; m; bird; 3; –; –; (26233). Old Swedish; foghl, foghil, fugh; m; bird; 3; –; –; (26341). Proto-Germanic; *fugla-; m; bird; 0; –; –; (60382). Swedish; fågel; c; bird; 3; –; –; (25513). PGm *kiukīnom, dim. of *kiuk-, *kuk- ‘cock’ (60500) Danish; kylling; c; chicken; 1; –; –; (60507). Dutch; kieken, kuiken; n; chick; 1; –; –; (60525). English; chicken; –; domestic fowl, esp. a young bird; domestic fowl prepared as food; meat of this bird; 1; –; –; (60528). German; Küchlein; n; chicken; 1; –; –; (60521). Icelandic; kjúklingur; m; chicken; 1; –; –; (60519). Irish; sicín; m; chicken; 2; Loan; English; (60534). Middle Dutch; kieken, kiekijn, kûken; n; chicken; 1; –; –; (60526). Middle English; chiken; –; chicken; 1; –; –; (60529). Middle High German; küchen; –; chicken; 1; –; –; (60522). Middle Low German; küken; n; chicken; 1; –; –; (60524). Norwegian (Bokmål); kjukling; m; chicken; 1; –; –; (60509). Norwegian (Bokmål); kylling; m; chicken; 2; Loan; Danish; (60511). Norwegian (Nynorsk); kjukling; m; chicken; 1; –; –; (60514). Norwegian (Nynorsk); kylling; m; chicken; 2; Loan; Danish; (60516).

460

Appendix 3b: Lexical data: Indo-European

Old English; cicen; n; the young of the hen; its meat; 1; –; –; (60530). Old Norse; kjúklingr; m; gosling; 3; –; –; (60501). Old Swedish; kyklinger; m; chicken; 1; –; –; (60502). Swedish; kyckling; c; chicken; 1; –; –; (60504). PCelt *yaro- ‘chicken, hen’ (60550) Breton; yar; f; hen; chicken (generic); 3; –; –; (60568). Cornish; yar; f; chicken; 1; –; –; (60573). Gaulish; Iaros; –; ?; 0; –; –; (60578). Irish; éaróg, éireog, iaróg; f; pullet, chicken, young hen; 1; –; –; (60551). Middle Breton; yar; –; hen; chicken (generic); 3; –; –; (60569). Middle Welsh; yar, iar, ieir, gieir; m,f; hen, chicken; hen; 3; –; –; (60560). Old Cornish; yar; –; chicken; 1; –; –; (60574). Old Irish; eirín, eiríne; m; chicken; 1; –; –; (60552). Old Welsh; iar; f; hen, chicken; hen; 3; –; –; (60561). Proto-Celtic; *yaro-; –; chicken, hen; 0; –; –; (60553). Scottish Gaelic; eireag; f; pullet, chicken, young hen; 1; –; –; (60554). Welsh; iar; f; hen; 3; –; –; (60559). Alb pulkë ‘pullet; turkey’ ← Bulg pulka ‘pullet’ (60580) Albanian (Tosk); pulkë; f; pullet; turkey; 2; Loan; Bulgarian; (60581). Bulgarian; púlka; f; pullet; 1; –; –; (60582). OPor frângão ‘juvenile rooster’ (60734) Old Portuguese; frângão; m; juvenile rooster; 3; –; –; (60736). Portuguese; frango; m; chicken; 1; –; –; (60735). Avestan; yār-; n; year; 0; –; –; (60727). Classical Greek; ὥρα; f; time, season; 0; –; –; (60625). German; Jahr; n; year; 0; –; –; (60612). Gothic; jer; n; year; 0; –; –; (60624). Middle High German; jār; n; year; 0; –; –; (60613). Old High German; jār; n; year; 0; –; –; (60614). Sanskrit; paryāríṇī-; f; cow which has its first calf after a year; 0; –; –; (60729). Albanian (Tosk); jariçkë; f; pullet, chick; 2; Loan; Bulgarian; (60626). Bulgarian; járe; –; kid; 0; –; –; (60693). Bulgarian; jarička; –; yearling; 0; –; –; (60627). Croatian; jȃr; m; spring; 0; –; –; (60676). Croatian; jȁra; f; great heat, mirage, spirit; 0; –; –; (60672). Croatian; jȁre; m; kid, young goat; 0; –; –; (60667). Czech; jaro; n; spring; 0; –; –; (60637). Czech; jeřátko; n; one and a half year-old sheep; 0; –; –; (60632). Latvian; jēre; f; one year old sheep, mother lamb; 0; –; –; (60715). Latvian; ję̃rs; m; lamb; 0; –; –; (60712).

Lithuanian; ė́ras; m; lamb; 0; –; –; (60718). Lithuanian; jė́ras; m; lamb; 0; –; –; (60721). Old Church Slavonic; jara; f; spring; 0; –; –; (60708). Old Church Slavonic; jarę; n; lamb; 0; –; –; (60703). Old Polish; jaro; n; spring, spring corn; 0; –; –; (60645). Old Russian; jara; f; spring; 0; –; –; (60658). Old Russian; jarę; n; lamb; 0; –; –; (60649). Polish; jar; m; spring, spring corn; 0; –; –; (60641). Proto-Balto-Slavic; *jeʔro-; –; –; 0; –; –; (60630). Proto-Indo-European; *Hieh₁-r-ěro; –; spring; 0; –; –; (60684). Proto-Slavic; *ěrę; n; young animal; 0; –; –; (60633). Proto-Slavic; *ěro; n; spring; 0; –; –; (60629). Proto-Slavic; *jarica; f; one-year-old creature; 0; –; –; (60628). Russian; jar’; m; fury; 3; –; –; (60654). Serbian; jȃr; m; spring; 0; –; –; (60689). Serbian; jȁra; f; great heat, mirage, spirit; 0; –; –; (60685). Serbian; jȁre; n; kid, young goat; 0; –; –; (60680). Slovene; jarȅ; n; lamb; 0; –; –; (60662). PSl *kȍkošь ‘hen’ (symb.?) (94383) Croatian; kȍkōš; f; hen; chicken (generic); 3; –; –; (59918). Polish; kokosz; f; hen; chicken (generic); 3; –; –; (59914). Serbian; kȍkōš; f; hen; chicken (generic); 3; –; –; (59920). Slovene; kokọ̑š; f; hen; chicken (generic); 3; –; –; (59916). copper Gr χαλκός ‘copper, bronze’, Hitt (ḫ)apalki- ‘iron’ (83402) Classical Greek; χαλκός; m; ore; copper, bronze; 1; –; –; (83404). Hittite; (ḫ)apalki-; n; iron; 3; –; –; (83406). Modern Greek; χαλκός; m; copper; 1; –; –; (83403). PIE *h₁roudho- < *h₁reudh- ‘red’ (83407) German; Erz; n; ore; bronze; 3; –; –; (83408). Middle Dutch; arut; n; ore; 3; –; –; (83420). Middle High German; erz, erze, eriz, erize; n; ore; 3; –; –; (83409). Old High German; aruz, ariz, aruzi, arizi; m,n; ore; 3; –; –; (83410). Proto-Germanic; *arut-; m; ore; 0; –; –; (83411). Lat cyprium ‘copper’, ‘Cyprean metal’ (83423) Albanian (Tosk); qipër; f; copper; bronze; 2; Loan; Latin; (83567). Breton; kouevr; m; copper; 2; Loan; French; (83513). Catalan; coure; m; copper; 1; –; –; (83553). Classical Greek; κύπριος; adj; of Cyprus, from Cyprus; 0; –; –; (83488).

Appendix 3b: Lexical data: Indo-European

Classical Greek; Κύπρος; f; Cyprus; 0; –; –; (83489). Cornish; kober; m; copper; 1; –; –; (83515). Danish; kobber; n; copper; 1; –; –; (83433). Dutch; koper; n; copper; 1; –; –; (83473). Elfdalian; kupär; m; copper; 1; –; –; (83448). English; copper; –; malleable and ductile metal, chemical symbol Cu; 1; –; –; (83482). Faroese; kopar; n; copper; 1; –; –; (83445). French; cuivre; m; copper; 1; –; –; (83514). German; Kupfer; n; copper; 1; –; –; (83451). Icelandic; kopar; m; copper; 1; –; –; (83442). Irish; copar; m; copper; 2; Loan; English; (83503). Italian; cùpreo; adj; of or pertaining to copper; 3; –; –; (83516). Italian; cuprico; adj; pertaining to copper; 3; –; –; (83522). Late Latin; *coprum; n; copper; 1; –; –; (83470). Late Latin; *cūbrum; n; copper (?); 3; –; –; (83554). Late Latin; cuprum; n; copper; 1; –; –; (83425). Late Latin; cuprum; n; copper; 1; –; –; (83432). Late Latin; cūprum; n; copper; 1; –; –; (83506). Latin; cupreum, cyprium; n; copper; copper (lit. Cyprian metal); copper; 2; Loan; Classical Greek; (83456). Latin; cŭprĕus; adj; of or pertaining to copper; 3; –; –; (83517). Latvian; kapars; m; copper; 4; Loan; Late Latin; (83569). Middle Dutch; coper; n; copper; 2; Loan; Late Latin; (83474). Middle English; coper; –; copper; 1; –; –; (83483). Middle High German; kupfer; n; copper; 1; –; –; (83452). Middle Low German; kopper; n; copper; 2; Loan; Late Latin; (83469). Norwegian (Bokmål); kobber, kopper; n,m; copper; 1; –; –; (83436). Norwegian (Nynorsk); kopar; m; copper; 1; –; –; (83439). Old English; coper, copor; n; copper; 2; Loan; Late Latin; (83484). Old French; coevre; m; copper; 1; –; –; (83529). Old High German; kupfar, chuphar, chupfar; n; copper; 1; –; –; (83453). Old Norse; koparr; m; kupfer; 2; Loan; Late Latin; (83424). Old Swedish; kopar, koppar; m; copper; 1; –; –; (83426). Portuguese; cobre; m; copper; 1; –; –; (83541). Proto-Germanic; *kuppar-; –; copper; 0; Loan; Late Latin; (83454). Romanian; cupru; n; copper; 1; –; –; (83547). Scottish Gaelic; copar; m; copper; 1; –; –; (83510). Spanish; cobre; m; copper; 1; –; –; (83535). Swedish; koppar; c; copper; 1; –; –; (83429). Welsh; copr, copor; m; copper; 2; Loan; English; (83511).

461

PIE *h₂éi-es- ‘metal, copper, bronze’ (83575) Albanian (Tosk); rem; m; copper; 2; Loan; Latin/ Italian; (83710). Avestan; aiiah-; n; metal, copper; 3; –; –; (83640). Breton; aram; –; bronze; 2; Loan; Late Latin; (83647). Bulgarian; aranija; –; pot; 0; Loan; Romanian; (83712). Catalan; aram; m; copper, bronze; 1; –; –; (83691). English; ore; –; unworked metal, crude metal; 3; –; –; (83612). French; airain; m; bronze; 1; –; –; (83663). German; ehern; adj; iron, brazen; 3; –; –; (83587). Gothic; ais, aiz, aizis; n; ore, copper, bronze; money, coin; 3; –; –; (83628). Icelandic; eir; n; brass, copper; 3; –; –; (83583). Italian; rame; m; copper; 1; –; –; (83653). Late Latin; aerāmen; n; copper, bronze; 1; –; –; (83648). Late Latin; aerāmen; n; copper; bronze; 1; –; –; (83706). Latin; aerāmentum; n; prepared copper or bronze; 1; –; –; (83649). Latin; aes, -ris; n; copper, bronze; money; 1; –; –; (83631). Middle Dutch; eer; n; copper, metal; 1; –; –; (83606). Middle English; ær, ore, wore; –; ore; 3; –; –; (83613). Middle High German; ēr; n; ore, iron; 3; –; –; (83592). Middle Low German; ēr, ēre; n; ore; metal; copper, brass; 3; –; –; (83603). Occitan; aram; m; bronze; 1; –; –; (83658). Old English; ǣren; adj; iron, brazen; 3; –; –; (83624). Old English; ār, ǣr; n; brass, bronze, copper; 3; –; –; (83614). Old French; arain; m; bronze; 1; –; –; (83664). Old High German; ēr; n; ore; copper, bronze; 3; –; –; (83593). Old High German; ērīn; adj; iron, brazen; 3; –; –; (83588). Old Norse; eir; n; copper, bronze, brass; 3; –; –; (83576). Old Saxon; ēr; n; ore; brass; 3; –; –; (83609). Old Spanish; arambre; m; wire; 0; –; –; (83675). Old Spanish; aramne; m; bronze; 1; –; –; (83676). Old Swedish; ēr; m; copper, bronze; 1; –; –; (83579). Oscan; aizniō; adj; made of bronze; 3; –; –; (83634). Persian; ɑhæn; –; iron; 3; –; –; (83642). Portuguese; arame; m; (formerly) brass; brass wire, (by extension) wire of any metal, esp. copper or iron; 3; –; –; (83681). Proto-Germanic; *aiza-; n; ore, brass; 0; –; –; (83577).

462

Appendix 3b: Lexical data: Indo-European

Proto-Germanic; *aizīna-; –; brazen; 0; –; –; (83589). Proto-Indo-European; *h₂éi-es-; –; –; 0; –; –; (83578). Proto-Indo-European; *h₂ei-os, *h₂ei-es-; –; metal (copper, bronze); 0; –; –; (83633). Proto-Italic; *ajos, *ajes-; –; bronze; 0; –; –; (83632). Provençal; aram, eram; m; copper, bronze; 1; –; –; (94206). Romanian; aramă; f; copper, bronze; 1; –; –; (83686). Sanskrit; áyas-; n; metal, copper; iron; 3; –; –; (83644). Spanish; alambre; m; metal wire; 0; –; –; (83674). Umbrian; ahesnes; adj; made of bronze; 3; –; –; (83637). PIE *HoHmo- ‘raw; raw metal’ (83714) Irish; cré-umha; m; bronze; 1; –; –; (83715). Irish; umha; m; copper; copper alloy; bronze; brass; 1; –; –; (83720). Old Irish; crédumae; m; bronze, alloy of copper, brass; 1; –; –; (83716). Old Irish; umae; n,m; copper, bronze; 1; –; –; (83717). Old Welsh; emid; m; copper, bronze; 1; –; –; (83741). Proto-Celtic; *omiyo-; –; copper, bronze; 0; –; –; (83718). Proto-Indo-European; *HoHmo-; –; raw; 0; –; –; (83719). Scottish Gaelic; criadh-umha; f; brass ore; clay; 3; –; –; (83728). Scottish Gaelic; umha; m; bronze, brass; 3; –; –; (83724). Welsh; efydd; m; bronze, brass; 1; –; –; (83740). ̀ ‘copper’ (uct. etym.) (83747) PSl *mědь Croatian; mjȅd; m; copper, brass; 3; –; –; (83756). Czech; měd’; f; copper; 1; –; –; (83748). Old Church Slavonic; mědь; f; copper; 1; –; –; (83762). Polish; miedź; f; copper; 1; –; –; (83750). ̀ Proto-Slavic; *mědь; f; copper; 0; –; –; (83749). Russian; med’; f; copper; 1; –; –; (83752). Serbian; mjȅd; m; copper, brass; 1; –; –; (83758). Slovene; mẹ̑d; f; ore, metal (esp. copper and alloys of copper); 3; –; –; (83754). MHG spīse ‘metal for casting’ (no etym.) (83764) German; Glockenspeise, Speise; f; alloy for bellcasting alloy; bell bronze; 3; –; –; (83765). Middle High German; glockenspīse; f; bell metal, cannon bronze; 3; –; –; (83766). Middle High German; spīse; f; metal for casting; 3; –; –; (83767). Polish; spiż; m; bell bronze, cannon bronze; hard alloy of copper, tin, zinc and lead; 4; Loan; Middle High German; (83770).

PBalt *var- ‘copper’ (← FU) (83772) Croatian; bàkar; m; copper; 2; Loan; Turkish; (83773). Latvian; varš; m; copper; 2; Loan; Finno-Ugric (branch)?; (83775). Lithuanian; vãrias, vãris; m; copper; 2; Loan; Finno-Ugric (branch)?; (83776). Lithuanian; žalvaris; m; bronze; 1; –; –; (83777). Old Prussian; wargien; –; copper; 2; Loan; FinnoUgric (branch)?; (83779). PGm *bras ‘metal, copper’ (migr.?) (83780) Cornish; brest; m; brass; 4; Loan; Middle English; (83799). English; brass; –; alloy of copper and zinc; 3; –; –; (83782). Irish; prás; m; brass; (formerly) generic bronze; 3; –; –; (83788). Middle English; bras; –; generic bronze; 1; –; –; (83783). Middle Irish; prás; m; brass; 4; Loan; Middle English; (83789). Middle Low German; bras-penniuk; –; silver coin; 0; –; –; (83781). Old English; bræs; n; generic bronze; 1; –; –; (83784). Scottish Gaelic; pràis; f; brass; 3; –; –; (83792). Welsh; pres; m; brass; 4; Loan; Middle English; (83796). TB pilke* ‘copper’ < TB pälk- ‘burn’ (83802) Tocharian B; pälk-; v; to burn (intr.); 0; –; –; (30717). Tocharian B; pilke*; –; copper; 1; –; –; (83803). cow PGm *farza(n)- ‘young bull’ < PIE *prh₃-o‘providing’ (54485) English; farrow; adj; (of cow) without calf; 0; –; –; (54546). Middle English; farrow; adj; (of cow) without calf; 0; –; –; (54547). PIE *gʷeh₃-u- ‘cow’ (54635) Avestan; gav-; f,m; cow; bull; cattle; 1; –; –; (54787). Avestan; gav-; m,f; cattle; bull; cow; 3; –; –; (54786). Breton; biou; pl; cattle; 3; –; –; (54860). Breton; buoc’h; f; cow; 1; –; –; (54856). Bulgarian; govédo; n; head of cattle; 1; –; –; (54819). Catalan; bou; m; ox; 3; –; –; (54762). Classical Greek; βοῦς; f,m; cow, bull, ox; (pl.) cattle; 1; –; –; (54782). Cornish; buch; m; cow; 1; –; –; (54870). Croatian; gòvedo; n; head of cattle; 1; –; –; (54812). Czech; hovado; n; head of cattle, cattle; 1; –; –; (54800). Danish; ko; c; cow; 1; –; –; (54648). Dutch; koe; c; cow; 1; –; –; (54691). Elfdalian; tjyr; f; cow; 1; –; –; (54668).

Appendix 3b: Lexical data: Indo-European

English; cow; –; fully grown female bovine, used as a source of milk and beef and for breeding; 1; –; –; (54701). English; kine; –; cattle; 3; –; –; (54706). Faroese; kúgv; f; cow; 1; –; –; (54664). French; boeuf; m; ox; bovine animal (generic); meat of this animal; 3; –; –; (54741). Frisian; ko; c; cow; 1; –; –; (54722). Friulian; bo; m,f; cow, ox; 1; –; –; (54770). German; Kuh; f; cow; 1; –; –; (54672). Hindi; gāu; m; bull, bullock; 3; –; –; (54793). Icelandic; kýr; f; cow; 1; –; –; (54660). Irish; bó; f; cow; 1; –; –; (54829). Irish; bó allaidh; f; wild ox; buffalo; 3; –; –; (54833). Irish; buar; mpl; cattle; 3; –; –; (54834). Italian; bue, bove; m; ox; 3; –; –; (54729). Latin; bōs; m,f; bovine animal, cattle; ox, bull; cow; 3; –; –; (54730). Latvian; govs, guovs; f; cow; 1; –; –; (54826). Low German; ko; f; cow; 1; –; –; (54684). Middle Breton; bou-tig; –; stable; 0; –; –; (54867). Middle Breton; buch; –; cow; 1; –; –; (54857). Middle Dutch; coe, kuo; f; cow; 1; –; –; (54692). Middle English; cowe, cow, cu, ku, cou, kou, kow, kowe, cough, coowe; –; cow; female of any bovine animal; 1; –; –; (54702). Middle English; kine; –; cattle (collective); 3; –; –; (54707). Middle High German; kuo; f; cow (generic & specific); 1; –; –; (54673). Middle Low German; kô; f; cow; 1; –; –; (54685). Middle Welsh; bu, buw, buch; f,m; cow; 1; –; –; (54850). Modern Armenian; kov; –; cow; 1; –; –; (54780). Norwegian (Bokmål); ku; m,f; cow; 1; –; –; (54652). Norwegian (Nynorsk); ku, kyr; f; cow; 1; –; –; (54656). Occitan; buou; m; ox; 3; –; –; (54737). Old Church Slavonic; govędo; n; head of cattle; 3; –; –; (54803). Old English; cū; f; cow; female of any bovine animal; 1; –; –; (54703). Old French; buef, beuf; m; castrated bull; meat of this animal; 3; –; –; (54742). Old Frisian; kū; f; cow; 1; –; –; (54723). Old High German; kuo, chuo; f; cow; 1; –; –; (54674). Old Irish; bó; f; ox; cow; 3; –; –; (54830). Old Norse; kýr; f; cow; 1; –; –; (54636). Old Persian; gav-; m,f; cow; cattle; 1; –; –; (93996). Old Saxon; kō; f; cow; 1; –; –; (54698). Old Swedish; ko; f; cow; 1; –; –; (54639). Ossetian (Iron); gal; –; bull; 3; –; –; (54784). Ossetian (Iron); qug; –; cow; 1; –; –; (54785). Portuguese; boi; m; bovine, bull, ox; 3; –; –; (54754). Proto-Celtic; *bow-; –; cow; 0; –; –; (54831).

463

Proto-Germanic; *kō-, *kū-; –; cow; 0; –; –; (54637). Proto-Indo-European; *gʷeh₃-; –; cow; 0; –; –; (54732). Proto-Indo-European; *gʷh₃-eu-; –; –; 0; –; –; (54802). Proto-Indo-European; *gʷōw-; –; cow; 0; –; –; (54832). Proto-Indo-European; *gwōw-, *gwōw-; –; cow; 0; –; –; (36986). Proto-Italic; *gʷous; –; –; 0; –; –; (54731). Proto-Slavic; *govę̀do; n; head of cattle; 0; –; –; (54801). Provençal; bou; boio; m,f; bull; cow; 3; –; –; (54766). Punjabi; gāu, gã;̄ f; cow; 1; –; –; (54794). Romanian; bou; m; ox; castrated bull used as a beast of burden; 3; –; –; (54758). Russian; govjádina; f; beef; 0; –; –; (54806). Sanskrit; *gāvā-; f; cow; 1; –; –; (54792). Sanskrit; gāus-; m,f; ox, cow; 3; –; –; (54788). Sanskrit; gávya-; –; butter; 0; –; –; (54789). Sanskrit; go-; m,f; cow, ox; 1; –; –; (54790). Sardinian; boe; m; ox; 3; –; –; (54733). Scottish Gaelic; bó; f; cow; fawn; 1; –; –; (54838). Scottish Gaelic; buar; mpl; cattle, oxen; herd of cattle; 3; –; –; (54842). Serbian; gòvedo; n; head of cattle; 1; –; –; (54816). Slovene; govę́dọ; n; head of cattle; 1; –; –; (54809). Spanish; buey; m; ox; fool; 3; –; –; (54750). Swedish; ko; c; cow; 1; –; –; (54643). Tocharian A; ko; f; cow; 1; –; –; (54795). Tocharian B; keu*; f; cow, adult female cow; 1; –; –; (54797). Umbrian; bus*; m; bovine animal; 3; –; –; (54777). Welsh; buwch; f; cow; 1; –; –; (54849). PIE *ueḱ-eh₂-, *uoḱ-eh₂- ‘bovine, cow’ (54873) French; vache; f; cow; 1; –; –; (54880). Italian; vacca; f; cow; 1; –; –; (54874). Latin; vacca; f; cow; 1; –; –; (54875). Occitan; vaca; f; cow; 1; –; –; (54878). Old French; vake, vache; f; cow; 1; –; –; (54881). Portuguese; vaca; f; cow; 1; –; –; (54887). Sardinian; bacca; f; cow; 1; –; –; (54876). Spanish; vaca; f; cow; 1; –; –; (54885). PIE *h₂eǵHo- ‘cow’ (54890) Avestan; azī-; –; with young (of cows or mares); milking (of cows and mares); 0; –; –; (54914). Classical Armenian; ezn; –; bullock; ox; 3; –; –; (54910). Irish; aighe, agh; m,f; cow; ox; 3; –; –; (54891). Middle Welsh; aelaw; m; riches, wealth; 0; –; –; (54906). Modern Armenian; ezn; –; bullock, ox; 3; –; –; (54909). Old Irish; ag; n,m,f; bovine animal; cow, ox; 3; –; –; (54892).

464

Appendix 3b: Lexical data: Indo-European

Old Irish; ag allad; m,f; deer; stag; 0; –; –; (54902). Proto-Celtic; *agos-; –; cow; 0; –; –; (54893). Proto-Indo-European; *(H)h₁eǵh-ih₂-m; –; –; 0; –; –; (54911). Proto-Indo-European; *h₁eǵh-; –; –; 0; –; –; (54915). Proto-Indo-European; *h₂eǵHo-; –; cow; 0; –; –; (54894). ́ f; cow; female of an animal; 1; –; Sanskrit; ahī-; –; (54916). Scottish Gaelic; àgadh; m; ox; 3; –; –; (54895). MoArm erinǰ ‘heifer, (young) cow’ (uct. etym.) (54918) Modern Armenian; erinǰ; –; heifer, young cow; cow; two-year old female calf; bride; 1; –; –; (54919). PArm *bor ‘brown animal, cow’ (?) (54920) Modern Armenian; borek; –; a dark-complexioned cow; 3; –; –; (54922). Sanskrit; babhru-; f; a reddish-brown cow; 3; –; –; (54924). PIE *bhero- ‘the brown one’ (62291) Old High German; bero; m; bear; 0; –; –; (54921). Lat bēstia ‘beast, animal’ (uct. etym.) (66759) English; beast; –; animal; quadruped, bovine, beast of burden; brutal person; 0; –; –; (66798). Middle English; best, beest, beeste; –; animal; 0; Loan; Old French; (66799). cultivated field PIE *h₂eǵ-ro- ‘uncultivated field, pasture’ (57679) Classical Greek; ἀγρός; m; field; 1; –; –; (57685). Danish; ager; c; arable land, cultivated field; 1; –; –; (81093). Dutch; akker; c; field; 1; –; –; (81132). Elfdalian; åker; m; uncultivated field; 3; –; –; (81113). English; acre; –; unit of measurement of the area of land; 0; –; –; (81142). Faroese; akur; m; cornfield; 1; –; –; (81109). German; Acker; m; field; 1; –; –; (81117). Gothic; akrs; m; field; 1; –; –; (81157). Icelandic; akur; m; field; 1; –; –; (81105). Latin; ager; m; field; field for cultivation; domain (public or private); area, district, territory; country as opposed to town; 1; –; –; (57680). Middle Dutch; acker; m; land; 3; –; –; (81133). Middle English; aker; –; field; 1; –; –; (81143). Middle High German; acker; m; field; 1; –; –; (81118). Middle Low German; acker; m,n; plowed land; 1; –; –; (81129). Modern Armenian; art; –; cornfield, tilled field, arable land; cornfield; 1; –; –; (81076). Modern Armenian; art-ak’-; –; outside; 0; –; –; (81078). Modern Greek; ἀγρός; m; field; 1; –; –; (81161). Norwegian (Bokmål); åker; m; arable land; 1; –; –; (81097).

Norwegian (Nynorsk); åker; m; arable land; crop; 1; –; –; (81101). Old English; æcer; m; field; 1; –; –; (81144). Old Frisian; ekker, ēker; m; field; 1; –; –; (81154). Old High German; acchar, ackar; m; field; 1; –; –; (81119). Old Norse; akr; m; field; 1; –; –; (81081). Old Saxon; akkar; m; field; 1; –; –; (81139). Old Swedish; aker; m; field; 1; –; –; (81084). Proto-Germanic; *akra-; m; field; 0; –; –; (81082). Proto-Indo-European; *h₂eǵ-ro-; –; field, uncultivated field, pasture; 3; –; –; (57681). Proto-Indo-European; *h₂ǵro-; –; –; 0; –; –; (81077). Sanskrit; ájra-; m; field, plain; plain; open field; 1; –; –; (57690). Swedish; åker; c; arable land, tilled land; field; 1; –; –; (81088). < PIE *h₂erh₃- ‘to plow’ (72491) Avestan; uruuarā-; f; plant, flora; 0; –; –; (81546). Classical Greek; ἄρουρα; f; arable land; sowingland, corn-lands; fields; 1; –; –; (74806). Classical Greek; ἀρόω; v; to plow, plant; 0; –; –; (72597). Czech; role; f; field, arable land; 1; –; –; (81576). Czech; rolí; n; field, arable land; 1; –; –; (81582). Irish; arbhar; m; cereal crop, corn (growing or before it is harvested); 0; –; –; (74778). Latin; arvum; n; plow-land, field; plowed land; 1; –; –; (74804). Modern Armenian; harawunk’; –; sowing-field, arable land; 1; –; –; (81542). Old Czech; rolí; f; field, arable land; 1; –; –; (81577). Old Irish; arbar, arbor; n; (generic) grain, corn; (in pl.) crops; 0; –; –; (74779). Old Russian; rólija, ról’ja; f; (corn-)field, plowed field; 1; –; –; (81593). Polish; rola; f; field, arable land; 1; –; –; (81588). Proto-Balto-Slavic; *arʔ-; –; –; 0; –; –; (72600). Proto-Celtic; *arawar, *arawen-; –; grain, cereal; cultivated field; 0; –; –; (74780). Proto-Indo-European; *h₂erh₃-; v; to plow; 0; –; –; (72601). Proto-Indo-European; *h₂erh₃-uo-; –; plowable; 0; –; –; (81541). Proto-Indo-European; *h₂erh₃wr-; –; field; 0; –; –; (74781). Proto-Italic; *ara/owo-; –; –; 0; –; –; (81540). Proto-Slavic; *oràti; v; to plow; 0; –; –; (72599). Proto-Slavic; *orlьja; f; field, arable land; 0; –; –; (81578). Sanskrit; urvárā-; f; arable land, field yielding crop; 1; –; –; (81548). Scottish Gaelic; arbhar; m; corn, growing or in sheaf; corn, grain (before threshing); 0; –; –; (74782). Welsh; erw; f; field; historical unit of measurement of area, corresponding to 1/4 acre; acre; 1; –; –; (74792).

Appendix 3b: Lexical data: Indo-European

Welsh; erwain; –; meadow-sweet; 0; –; –; (74795). PIE *seg- ‘to attach, to touch, to sow’ (73047) Latin; seges, segetis; f; field of corn, sowing field, arable land; field of corn, arable land; 1; –; –; (73063). Proto-Italic; *seg-et-; –; seed; sown land; 0; –; –; (73064). PIE *der-ueh₂- ‘grass’ (?) (73288) Lithuanian; dirvà, dirvózě mis; f; soil, earth; (arable) land, field; 3; –; –; (73310). PIE *pelth₂- ‘flat’ (81169) Avestan; ząm pərəϑβīm; f; broad earth; 3; –; –; (81244). Bulgarian; polé; n; plain, field; 3; –; –; (81376). Croatian; pȍlje; n; plain, field; 3; –; –; (81372). Czech; pole; n; plain, field; 3; –; –; (81364). Danish; felt; n; partitioned piece of land; 2; Loan; Middle Low German; (81180). Dutch; veld; n; field; 1; –; –; (81197). English; field; –; a piece of ground, usually enclosed or demarcated, and put to a particular use; 1; –; –; (81207). Faroese; fold; f; (poetic): earth, ground, field, the world; 3; –; –; (81234). German; Feld; n; field; 1; –; –; (81182). Icelandic; fold; f; earth; ground, land; 3; –; –; (81230). Middle Dutch; veelt, velt, veld; n; field, plain; 3; –; –; (81198). Middle English; feeld; –; field, open land; the country as opposed to the town; 3; –; –; (81208). Middle High German; velt; n; field; 1; –; –; (81183). Middle Low German; velt; n; field, plain; 1; –; –; (81179). Norwegian (Nynorsk); fold; f; land beside river or sea; 3; –; –; (81226). Old Church Slavonic; polje; n; plain, field; 3; –; –; (81378). Old English; feld, feald; m; field; 1; –; –; (81209). Old English; folde; f; earth, ground, field, the world; 3; –; –; (26109). Old Frisian; feld; n; field; 1; –; –; (81219). Old High German; feld; n; field; 1; –; –; (81184). Old Norse; fold; f; earth, ground, field, the world; 3; –; –; (26024). Old Saxon; feld; m; field; 1; –; –; (81204). Old Saxon; folda; f; earth, ground, field, the world; 3; –; –; (26251). Old Swedish; fælt; n; field; 2; Loan; Middle Low German; (81178). Old Swedish; fiælder, urfiælder; m; plot of land; partitioned piece of land; 3; –; –; (81170). Polish; pole; n; plain, field; 3; –; –; (81366). Proto-Germanic; *felþa-; m; field; 0; –; –; (81171). Proto-Germanic; *fuldō-; f; earth, ground, field, the world; 0; –; –; (81224). Proto-Indo-European; *pélth₂-o-; –; –; 0; –; –; (81172).

465

Proto-Indo-European; *plth₂-éh₂-; –; –; 0; –; –; (25273). Proto-Indo-European; *plth₂-u-ih₂-; –; –; 0; –; –; (81245). Proto-Slavic; *pȍļe; n; field; 0; –; –; (81365). Russian; póle; n; plain, field; 3; –; –; (81368). ́ pr̥thivī-; ́ f; earth, Mother Earth; Sanskrit; pr̥thvī-, 3; –; –; (81246). Serbian; pȍlje; n; plain, field; 3; –; –; (81374). Slovene; pọ̑lje, poljȇ; n; field; 1; –; –; (81370). Swedish; fält; n; field; 1; –; –; (81177). PIE *uólH-tu- < *uelH- ‘to undulate’ (81248) Croatian; vlȃt; f; panicle; 0; –; –; (81351). Czech; vlať; f; panicle (of oats); 0; –; –; (81341). Dutch; woud; n; wood; 0; –; –; (81296). Elfdalian; wall; m; pasture, grassland, field; 3; –; –; (81277). English; wold; –; high open uncultivated land or moor; 3; –; –; (81306). Faroese; vøllur; m; sward; grassy field; 3; –; –; (81273). German; Wald; m; wood; 0; –; –; (81281). Icelandic; völlur; m; field, grounds; 1; –; –; (81269). Irish; folt; m; hair (of head); locks, tresses; 0; –; –; (32516). Lithuanian; váltis; f; panicle (of oats); 0; –; –; (81357). Middle Dutch; wout, wolt, walt; n; wood, forest; 0; –; –; (81297). Middle English; wald, wæld; –; woodland; 0; –; –; (81307). Middle High German; walt; m; wood; 0; –; –; (81282). Middle Low German; wolt, walt; m,n; wood, forest; 0; –; –; (81293). Middle Welsh; gwallt; m; hair (of head); hair; 0; –; –; (32929). Norwegian (Bokmål); voll; m; grassland; 3; –; –; (81261). Norwegian (Nynorsk); voll; m; grassland; 3; –; –; (81265). Old Breton; guolt; –; hair; 0; –; –; (32856). Old Cornish; gols; –; hair; 0; –; –; (32887). Old Czech; vlať; –; ear; 0; –; –; (81342). Old English; weald; m; wood; 0; –; –; (81308). Old Frisian; wald; m,n; wood; 0; –; –; (81318). Old High German; wald; m; wood; 0; –; –; (81283). Old Irish; folt; m; hair (of head); foliage (poetic); 0; –; –; (32666). Old Norse; vǫllr; m; plain, field, meadow; 3; –; –; (81249). Old Prussian; wolti; –; ear (of corn); 0; –; –; (81360). Old Saxon; wald; m; wood; 0; –; –; (81303). Old Swedish; vallr, valdr; m; grassland, field, land; 3; –; –; (81252). Proto-Balto-Slavic; *wolʔtis; –; –; 0; –; –; (81358). Proto-Celtic; *wolto-; –; hair; 0; –; –; (81323).

466

Appendix 3b: Lexical data: Indo-European

Proto-Germanic; *walþu-; m; field, uncultivated area, wood; 0; –; –; (81250). Proto-Indo-European; *uol(H)-t-; –; hair; 0; –; –; (81344). Proto-Indo-European; *wol-t-; –; hair; 0; –; –; (81324). Proto-Slavic; *vȏltь; –; –; 0; –; –; (81343). Scottish Gaelic; falt, fuilt, fuiltean; f; human hair; locks, tresses; 0; –; –; (32573). Serbian; vlȃt; f; panicle; 0; –; –; (81354). Slovene; vlȃt; f,m; ear, panicle; 0; –; –; (81348). Swedish; vall; c; pasture, grassland, field; 3; –; –; (81256). PIE *dr(H)-u- ‘field, grass’ (81380) Latvian; dìrva; f; (arable) land, field; 1; –; –; (81386). Old Russian; derévnja; –; village, field; 0; –; –; (81382). Proto-Balto-Slavic; *dir(ʔ)w-; –; –; 0; –; –; (81384). Proto-Indo-European; *dr(H)-u-; –; –; 0; –; –; (81385). Proto-Slavic; *dьrvьņa; f; field; 0; –; –; (81383). Russian; derévnja; f; village, (dial.) field, wasteland, plowed field; 0; –; –; (81381). Sanskrit; dū́rvā-; –; grass, Panicum dactylon; panic grass; 0; –; –; (73312). < PIE *meǵh₂- ‘great’ (81394) Breton; ma; –; place; 0; –; –; (81416). Breton; maes; m; plain; field for cultivation; 3; –; –; (81418). Cornish; -ma; –; plain, field; 3; –; –; (81430). Gaulish; *magus; –; plain, field; 3; –; –; (81433). Irish; amach, amuigh; adv; out; outside; 0; –; –; (81399). Irish; mágh; f; plain, field; 3; –; –; (81395). Middle Breton; maes; –; field; 1; –; –; (81419). Middle Welsh; -ma, maes; m; plain; field for cultivation; 3; –; –; (81409). Old Breton; -ma; –; plain, field; 3; –; –; (81417). Old Irish; immaig; adv; outside; 0; –; –; (81400). Old Irish; mag; n; plain, field; 3; –; –; (81396). Old Welsh; maessid; –; plain, field; 3; –; –; (81410). Proto-Celtic; *magos-; –; plain, field; 0; –; –; (81397). Proto-Indo-European; *meǵh₂-; –; great; 0; –; –; (37363). ́ f; earth; 3; –; –; (81436). Sanskrit; mahī-; Scottish Gaelic; magh; m; field; plain; battlefield; 3; –; –; (81401). PIE *(H)rewHos- ‘open space’ (81437) Avestan; rauuah-; –; space, room; 0; –; –; (81451). Irish; ré, réidh, rae; f; level plain, field, stretch of level ground; 3; –; –; (32548). Latin; rūs; n; village, countryside; 0; –; –; (81450). Old English; rūm; n; space, room; 0; –; –; (81438).

Old Irish; róe; f; level, piece of ground, battlefield, battle; 3; –; –; (81440). Proto-Celtic; *rowesyā; –; field, open ground; 0; –; –; (81441). Proto-Indo-European; *(H)rewHos-; –; open space; 0; –; –; (81442). Scottish Gaelic; réidh; adj; plain, level, smooth; 3; –; –; (81443). PItal *kampo- ‘field’ (uct. etym.) (81452) Catalan; camp; m; field for cultivation; 1; –; –; (81474). Classical Greek; καμπή; f; bow, curvature; 0; –; –; (81486). Classical Greek; κάμπτω; v; to bend, curve; 0; –; –; (81485). French; champ; m; field for cultivation; 1; –; –; (81462). Friulian; čhamp; m; field for cultivation; 1; –; –; (81480). Italian; campo; m; field for cultivation; 1; –; –; (81453). Latin; campus; m; flat land, plain, open field; (specialised:) field for cultivation; 1; –; –; (81454). Occitan; camp; m; field for cultivation; 1; –; –; (81459). Portuguese; campo; m; plain; flat ground, esp. for cultivation; 3; –; –; (81468). Proto-Italic; *kampo-; –; field; 0; –; –; (81455). Provençal; campo; m,f; field for cultivation; 1; –; –; (81477). Romanian; cîmp; m; field for cultivation; 1; –; –; (81471). Sardinian; kampu; m; field for cultivation; 1; –; –; (81456). Spanish; campo; m; field for cultivation; 1; –; –; (81465). PItal * kʷele/o- < PIE *kʷlh₁- ‘go round’ (81487) French; culture; f; the work of cultivating the soil; the techniques and methods; (metonymy, generally in plural) cultivated piece of ground; 3; –; –; (81488). Latin; colere; v; to live in, inhabit; to take care of, honour; 0; –; –; (81491). Latin; cultūra; f; cultivation, tillage, piece of cultivated land, care bestowed on plants, mode of growing plants, training or improvement of the faculties, observance of religious rites, veneration of a person, training of the body; 0; –; –; (81489). Latin; cultus; m; labor, care; 0; –; –; (81490). Portuguese; cultura; f; the act, work, or process of cultivating the land; cultivation; a cultivated piece of ground; the knowledge, creations, manners etc of a person or a social group; 3; –; –; (81494). Proto-Indo-European; *kʷelh₁-e/o-; v; to go round; 0; –; –; (81493). Proto-Italic; *kʷele/o-, kʷolō-no-?; –; –; 0; –; –; (81492).

Appendix 3b: Lexical data: Indo-European

< PIE *seg-e/o- ‘to adhere’ (81505) Middle Welsh; hëu; v; to sow, throw on, strew; 0; –; –; (81506). Proto-Celtic; *seg-(y)e/o-; –; –; 0; –; –; (81507). Proto-Italic; *seg-e/o-; v; to adhere, fasten; 0; –; –; (81510). ClArm and ‘arable field’ < PIE *h₂endh- ‘to sprout’ (81511) Classical Armenian; and; –; cornfield, arable field; pastureland (dial.); estate; 1; –; –; (81512). Proto-Indo-European; *h₂endh-; –; –; 0; –; –; (81513). PIE *h₂eh₁s-iōn- ‘dried land’ (?) < PIE *h₂eh₁s-eh₁‘to be dry’ (81514) Albanian (Tosk); arë; f; field; 1; –; –; (81519). Latin; ārea; f; ground, space, threshing floor; 3; –; –; (81515). Latin; ārēre; v; to be dry; 0; –; –; (81516). Proto-Albanian; *arā; –; –; 0; –; –; (81520). Proto-Indo-European; *h₂eh₁s-eh₁-; v; to be dry; 0; –; –; (81518). Proto-Italic; *ās-ē-; v; to be dry; 0; –; –; (81517). PSl ņìva ‘field’ (uct. etym.) (81550) Bulgarian; níva; ; field, plowed field; 1; –; –; (81569). Croatian; njȉva; f; field, plowed field; 1; –; –; (81563). Czech; niva, níva; f; field, plowed field, floodplain; 1; –; –; (81551). Old Church Slavonic; niva; f; field; 1; –; –; (81572). Polish; niwa; f; field (poet.); corn-field; 1; –; –; (81554). Proto-Indo-European; *neh₁i-u-?; –; –; 0; –; –; (81553). Proto-Slavic; *ņìva; f; field; 0; –; –; (81552). Russian; níva; f; (corn-)field; 1; –; –; (81557). Serbian; njȉva; f; field, plowed field; 1; –; –; (81566). Slovene; njíva, gnjiva; f; field, plowed field; 1; –; –; (81560). Alb tokë ‘field’ ← PSl *tokь ‘threshing floor’ (81598) Albanian (Tosk); tokë; f; earth, land soil, ground, plot of land, field; 4; Loan; Proto-Slavic; (81599). Proto-Slavic; *tokь; –; threshing floor; 0; –; –; (81600). TB mīṣe ‘field’ ← Khot (81601) Khotanese; miṣṣa-; –; field; 1; –; –; (81603). Tocharian A; miṣi; m; field; 2; Loan; Khotanese; (81602). Tocharian B; mīṣe; msg; field; 2; Loan; Khotanese; (81604). Hitt tereppi- ‘plowed field’ < PIE *trép- ‘to turn’ (81606) Hittite; tere/ippi-; n; plowed field; 1; –; –; (81607). Proto-Indo-European; *trép-/*trp-; v; to turn; 0; –; –; (81608).

467

No etym. (–) Middle Persian; warzbūm; –; cultivated field, cultivated land; 1; –; –; (94014). deer PIE *ḱer(h₂)-uo-/-ueh₂- ‘horned animal’ (55066) Avestan; sruuā-; f; horn, nail; 0; –; –; (66521). Breton; karw; m; deer; 1; –; –; (66401). Bulgarian; kráva; f; cow; 0; –; –; (66507). Bulgarian; sǎrná; f; roe deer; 3; –; –; (66742). Catalan; cérvol; m; deer; 1; –; –; (66452). Classical Greek; κεραός; adj; horned; made of horn; 0; –; –; (66481). Classical Greek; κέρας; n; horn; 0; –; –; (66479). Cornish; karow; m; deer, stag; 1; –; –; (66408). Croatian; krȁva; f; cow; 0; –; –; (66499). Croatian; sŕna; f; roe deer; 3; –; –; (66734). Czech; kráva; f; cow; 0; –; –; (66483). Czech; srna; f; female roe deer; 3; –; –; (66717). Danish; hjort; c; deer (generic); male deer; 1; –; –; (66541). Danish; kronhjort; c; red deer; 3; –; –; (66545). Dutch; hert; n; red deer; deer (generic); male deer; 3; –; –; (66589). Elfdalian; juort; m; deer; 1; –; –; (66566). English; hart; –; male deer, esp. red deer; 3; –; –; (66603). Faroese; hjørtur; m; deer (generic), male deer; 1; –; –; (66562). French; cerf; m; deer, stag; 1; –; –; (66431). Friulian; cierv; m; deer, buck; 1; –; –; (66472). Gaulish; *caru-; –; deer (?); 1; –; –; (66416). Gaulish; Caruus; –; –; 0; –; –; (66415). German; Hirsch; m; deer (generic); male deer; venison; 1; –; –; (66570). Hittite; karāu̯ar, karaun-; n; horn(s), antlers; 0; –; –; (66525). Icelandic; hjörtur; m; deer (generic), male deer; 1; –; –; (66558). Irish; cairrfhiadh ruadh; m; a red deer; 3; –; –; (66382). Irish; carria, cairrfhiadh; m; a hart, a wild deer; 1; –; –; (66380). Italian; cervo; m; deer, stag; 1; –; –; (66419). Ladin; cerf; –; deer; 1; –; –; (66468). Latin; cervus; m; stag, deer; 1; –; –; (63702). Latvian; stirna; f; roe deer; 3; –; –; (66750). Lithuanian; kárvė; f; cow; 0; –; –; (66515). Lithuanian; stìrna; f; roe deer; 3; –; –; (66753). Low German; hart; m; deer; 1; –; –; (66582). Middle Breton; caru; –; deer; 1; –; –; (66402). Middle Dutch; hert, hart; m; deer (generic); male deer; 1; –; –; (66590). Middle Dutch; hertinne; f; female deer; 1; –; –; (66596). Middle English; hert, hart; –; the male of the (red) deer; 3; –; –; (66604). Middle High German; hirȥ; m; deer (generic); male deer; 1; –; –; (66571). Middle Low German; harte, herte; n; deer (generic); 1; –; –; (32371). Middle Welsh; carw; m; deer; 1; –; –; (66389).

468

Appendix 3b: Lexical data: Indo-European

Norwegian (Bokmål); hjort; m; red deer; 3; –; –; (66550). Norwegian (Nynorsk); hjort; m; red deer; 3; –; –; (66554). Occitan; cerf, cèrvi; m; deer, stag; 1; –; –; (66427). Old Church Slavonic; krava; f; cow; 0; –; –; (66511). Old Church Slavonic; srъna; f; roe deer; 3; –; –; (66746). Old Cornish; caruu; –; deer; 1; –; –; (66409). Old English; heorot, heort; m; hart, male deer; 1; –; –; (66605). Old French; cerf; m; deer; 1; –; –; (66432). Old Frisian; hert; m; stag, deer; 1; –; –; (66615). Old High German; hiruz, hirz; m; deer; 1; –; –; (66572). Old Irish; *carr; –; deer; 1; –; –; (66385). Old Irish; cairrḟiad; m; stag; 1; –; –; (66381). Old Norse; hjǫrtr; m; deer; 1; –; –; (66528). Old Prussian; curwis; –; ox; 0; –; –; (66518). Old Prussian; sirwis; –; roe deer; 3; –; –; (66756). Old Saxon; hirot, hirut; m; stag; 1; –; –; (66600). Old Swedish; hiorter; m; deer; 1; –; –; (66531). Old Welsh; caru; m; deer; 1; –; –; (66390). Polish; krowa; f; cow; 0; –; –; (66487). Polish; sarna; f; roe deer; 3; –; –; (66721). Portuguese; cervo; m; deer (generic); 1; –; –; (66444). Proto-Balto-Slavic; *kórʔveʔ; –; –; 0; –; –; (66485). Proto-Balto-Slavic; *śírʔnaʔ; –; –; 0; –; –; (66719). Proto-Celtic; *karwo-; m; deer; 0; –; –; (66386). Proto-Germanic; *heruta-; m; stag, hart, deer; 0; –; –; (66529). Proto-Indo-European; *ḱer(h₂)-uo-; –; having horns; 0; –; –; (63704). Proto-Indo-European; *ḱer-n-, *ḱerh₂-; –; horn; head; 0; –; –; (66387). Proto-Indo-European; *ḱorh₂-ueh₂, *ḱorh₂-ueh₂-; –; –; 0; –; –; (66486). Proto-Indo-European; *ḱr-; –; horn; 0; –; –; (66530). Proto-Indo-European; *ḱrh₂-neh₂, *ḱrh₂-neh₂-; –; –; 0; –; –; (66720). Proto-Indo-European; *ḱr̥h₂só-; –; horned one; 0; –; –; (67488). Proto-Italic; *kerwo-, *kerawo-; –; horned animal, stag; 0; –; –; (63703). Proto-Slavic; *kòrva; f; cow; 0; –; –; (66484). Proto-Slavic; *sьrna; f; roe deer; 0; –; –; (66718). Provençal; cerf, cèrvi; m; deer; 1; –; –; (66456). Romanian; cerb; m; deer; 1; –; –; (66448). Romansh; tschierv; –; deer; 1; –; –; (66464). Russian; koróva; f; cow; 0; –; –; (66491). Russian; sérna; f; chamois; 3; –; –; (66725). Sanskrit; śiras-; n; head, chief, foremost, top; 0; –; –; (66523). Sardinian; chelvu, cherbu, chervu; m; deer; 1; –; –; (66423). Serbian; krȁva; f; cow; 0; –; –; (66503).

Serbian; sŕna; f; roe deer; 3; –; –; (66738). Slovene; kráva; f; cow; 0; –; –; (66495). Slovene; srna; f; female roe deer; 3; –; –; (66729). Slovene; srnjak; m; roebuck; male roe deer; 3; –; –; (66733). Spanish; ciervo; m; deer, stag; 1; –; –; (66440). Swedish; hjort; c; deer (generic); male deer; 1; –; –; (66536). Swedish; kronhjort; c; red deer; 3; –; –; (66535). Tocharian B; karse; m; deer, stag; 1; –; –; (67487). Walloon; ciér; –; deer; 1; –; –; (66460). Welsh; carw; m; deer; 1; –; –; (66388). Welsh; carw coch; m; red deer; 3; –; –; (66393). PIE *dmh₂o- ‘tamed animal, ox’ (55146) Middle High German; dam; m; fallow deer; 3; –; –; (55148). PIE *dheh₁-to- ‘having given birth’ (57224) English; fawn; –; young (fallow) deer; 3; –; –; (67458). French; faon; m; young of the deer; 3; –; –; (67471). Latin; fētus; adj; having recently given birth; fertile; 0; –; –; (57226). Latin; fētus; m; parturition, breeding, offspring; 0; –; –; (57229). Middle English; foun, faon, faune, fawn; –; young animal; young fallow deer; 0; Loan; Old French; (67459). Old French; faon, faün; m; young of a wild animal; young deer; 3; –; –; (67460). Proto-Indo-European; *dheh₁-to-; –; having given birth; 0; –; –; (57228). Proto-Italic; *fēto-; –; –; 0; –; –; (57227). PIE *h₃éu-i- ‘sheep’ (57237) Welsh; ewig; f; female of various species of deer; hind, doe; 3; –; –; (57318). < PIE *ḱem- ‘to truncate (horns)’ (58071) Classical Greek; κεμάς, -άδος; f; young deer, young dog, pricket; 3; –; –; (66710). Danish; hind; c; female (red or sika) deer; 1; –; –; (66634). Dutch; hinde; c; female deer; 1; –; –; (66678). English; hind; –; female deer, esp. red deer; 1; –; –; (66691). Faroese; hind; f; female deer; 1; –; –; (66654). German; Hinde; f; female deer; 1; –; –; (66659). Icelandic; hind; f; female deer; 1; –; –; (66649). Middle Dutch; hinde; f; female deer; 1; –; –; (66679). Middle English; hind; –; female (red) deer; 3; –; –; (66692). Middle High German; hinde; f; female deer; 1; –; –; (66660). Middle Low German; hinde; f; female deer; 1; –; –; (66674). Norwegian (Bokmål); hind; m,f; female deer; 1; –; –; (66639). Norwegian (Nynorsk); hind; f; female deer; 1; –; –; (66644).

Appendix 3b: Lexical data: Indo-European

Old English; hind; f; female deer; 1; –; –; (66693). Old Frisian; hinde; f; female deer; 1; –; –; (66706). Old High German; hinta; f; female deer; 1; –; –; (66661). Old Norse; hind; f; female deer; 1; –; –; (66619). Old Swedish; hind; f; female deer; 1; –; –; (66623). Proto-Germanic; *hindō-; f; hind; 0; –; –; (66620). Proto-Indo-European; *ḱem-; v; to truncate (horns); 0; –; –; (58076). Proto-Indo-European; *ḱem-nd-o-; –; –; 0; –; –; (66711). Proto-Indo-European; *ḱem-teh₂-; –; –; 0; –; –; (66621). Sanskrit; śáma-; adj; hornless; 0; –; –; (58148). Swedish; hind; c; female deer; 1; –; –; (66628). PIE *h₁el- ‘deer’ (58394) Bulgarian; álne; f; young chamois; 3; –; –; (67045). Bulgarian; jelén; m; deer (generic); 1; –; –; (67135). Classical Armenian; analut’; –; a kind of deer, hind; probably fallow deer; 3; –; –; (67021). Classical Armenian; ełn; –; deer; 1; –; –; (67097). Classical Greek; ἐλάφιον; n; young deer, deer calf; 3; –; –; (67102). Classical Greek; ἔλαφος; m,f; deer, deer cow; 1; –; –; (67103). Classical Greek; ἔλενος, ἔνελος; m; young of the deer, fawn; 3; –; –; (67109). Classical Greek; ἐλλός; m; fawn; 3; –; –; (67107). Croatian; jèlen; m; deer (generic), stag-beetle; 1; –; –; (67127). Croatian; lȁne; n; fawn; 1; –; –; (67036). Croatian; lanjac; m; fallow deer; 3; –; –; (67035). Czech; jelen; m; deer, stag-beetle; 1; –; –; (67111). Czech; laň; f; doe; 1; –; –; (67023). Czech; los; m; elk; 3; –; –; (67189). Danish; elg; c; elk, moose; 3; –; –; (67169). English; elk; –; large deer, Alces alces, also called moose; 3; –; –; (67221). Faroese; elgur; m; elk, moose; 3; –; –; (67185). Gaulish; Elantia; –; –; 0; –; –; (67093). German; Elch; m; elk, moose; 3; –; –; (67206). Icelandic; elgur; m; elk, moose; 3; –; –; (67181). Irish; eilit; f; doe, hind; 1; –; –; (67075). Italian; alce; m; elk, moose; 3; –; –; (67235). Latin; alcēs; f; elk, moose; 4; Loan; ProtoGermanic; (67236). ̄ Latvian; alnis; m; elk; 3; –; –; (67053). Lithuanian; álnė; f; doe; 3; –; –; (67068). Lithuanian; álnis; m; deer; 3; –; –; (67065). Lithuanian; elenis; m; deer; 1; –; –; (67143). Lithuanian; élnė; f; doe; 1; –; –; (67056). Lithuanian; élnias; m; deer; 1; –; –; (67059). Lithuanian; élnis; m; deer; 3; –; –; (67062). Low German; elk; m; elk, moose; 3; –; –; (67218). Middle English; elke, alke; –; elk, moose; 4; Loan; Middle High German; (67222).

469

Middle High German; elch, elhe; m; elk, moose; 3; –; –; (67207). Middle Welsh; elein, alanet; f,m; young deer, doe, hind-calf; 3; –; –; (67087). Modern Armenian; analut’; –; a kind of deer, hind; probably fallow deer; 3; –; –; (67019). Modern Armenian; ełn; –; deer; 1; –; –; (67096). Modern Greek; ελάφι; n; deer (Cervus elaphus); 1; –; –; (67101). Norwegian (Bokmål); elg; m; elk, moose; 3; –; –; (67173). Norwegian (Nynorsk); elg; m; elk, moose; 3; –; –; (67177). Old Church Slavonic; alъnii*; f; doe (pl); 1; –; –; (67049). Old Church Slavonic; jelenь; m; deer; 1; –; –; (67139). ̆ la; m; elk, moose; 3; –; –; Old English; eolh, ēo (67232). Old High German; elaho, elho; m; elk, moose; 3; –; –; (67208). Old Irish; elit, ailit; f; doe, hind; 1; –; –; (67076). Old Norse; elgr; m; elk, moose; 3; –; –; (67153). Old Prussian; alne; –; wild animal; 0; –; –; (67071). Old Russian; losь; m; elk; 3; –; –; (67198). Old Swedish; ælgher; m; elk, moose; 3; –; –; (67156). Polish; jeleń; m; deer (generic); red deer; 1; –; –; (67115). Polish; ɫania; f; doe; 1; –; –; (67027). Polish; ɫoś; m; elk; 3; –; –; (67193). Portuguese; alce; m,f; elk, moose; 3; –; –; (67243). Proto-Balto-Slavic; *elenios; –; –; 0; –; –; (67113). Proto-Balto-Slavic; *ol-Hn-; –; –; 0; –; –; (67025). Proto-Celtic; *elanī; –; doe, hind; 0; –; –; (67088). Proto-Celtic; *elantī; –; doe, hind; 0; –; –; (67077). Proto-Germanic; *algi-; m; elk; 0; –; –; (67154). Proto-Germanic; *algjōn-; –; elk cow; 0; –; –; (67166). Proto-Germanic; *elha-, *elhan-; m; elk, moose; 0; –; –; (67209). Proto-Indo-European; *h₁(o)l-Hn-th₂o-; –; deer, hind; 0; –; –; (67020). Proto-Indo-European; *h₁el-; –; deer; 0; –; –; (67192). Proto-Indo-European; *h₁el-(h₁)en-; –; –; 0; –; –; (67098). Proto-Indo-European; *h₁el-h₁en-i-; –; –; 0; –; –; (67114). Proto-Indo-European; *h₁elh₁eno-; –; –; 0; –; –; (67110). Proto-Indo-European; *h₁elh₁nih₂-; –; female elk; female red deer; 0; –; –; (67078). Proto-Indo-European; *h₁el-ḱo(n)-; –; –; 0; –; –; (67210). Proto-Indo-European; *h₁el-n̥-; –; –; 0; –; –; (67148).

470

Appendix 3b: Lexical data: Indo-European

Proto-Indo-European; *h₁l-ḱ-io-; –; –; 0; –; –; (67203). Proto-Indo-European; *h₁ol-Hn-iH-; –; –; 0; –; –; (67026). Proto-Indo-European; *h₁ol-ḱ-i-; –; –; 0; –; –; (67155). Proto-Slavic; *eleņь; m; deer; 0; –; –; (67112). Proto-Slavic; *òlni; f; doe; 0; –; –; (67024). Proto-Slavic; *ȏlsь; m; elk; 0; –; –; (67190). Proto-Tocharian; *yälä; –; –; 0; –; –; (67147). Russian; lan’; f; fallow deer, doe; 3; –; –; (67031). Russian; los’; m; elk; the Great Bear; 3; –; –; (67197). Russian; olén’; m; deer, stag-beetle; 1; –; –; (67119). Sanskrit; ŕ̥śya-; m; male antelope; 0; –; –; (67202). Scottish Gaelic; eilid; f; hind, female of the red deer, roe; 3; –; –; (67079). Serbian; jèlen; m; deer (generic), stag-beetle; 1; –; –; (67131). Serbian; lȁne; n; fawn; 1; –; –; (67041). Serbian; lánjac; m; fallow deer; 3; –; –; (67040). Slovene; jélen; m; deer (generic), stag-beetle; 1; –; –; (67123). Spanish; alce; m; elk, moose; 3; –; –; (67239). Swedish; älg; c; elk, moose; 3; –; –; (67160). Swedish; elgja, ilgja; f; elk cow; 3; –; –; (67165). Tocharian A; yäl; m,f; deer; 1; –; –; (67146). Tocharian B; yal; fpl; deer; 1; –; –; (67149). Welsh; elain; f; hind-calf; fawn; 3; –; –; (67086). PIE *widhu- ‘wood’ (64563) Irish; fia; m; deer; 1; –; –; (66346). Irish; fia buí; m; fallow deer; 3; –; –; (66352). Irish; fia fionn; m; roebuck, fallow deer; 3; –; –; (66353). Old Irish; fíad; m; wild animal, deer; game; 0; –; –; (66347). Old Irish; fid; m; wood; tree; forest; 0; –; –; (66349). Proto-Celtic; *widu-; –; wood; 0; –; –; (66350). Proto-Indo-European; *widhu-, *widhu-; –; wood; 0; –; –; (37557). Scottish Gaelic; fiadh; m; deer, red deer; 1; –; –; (66354). Pers gævæzn ‘deer’ (uct. etym.) (66254) Persian; gævæzn; –; deer; 1; –; –; (66255). PGm *deuza- ‘(wild) animal’ (uct. etym.) (66256) Danish; dyr; n; animal; 0; –; –; (66270). Dutch; dier; n; (wild) animal; 0; –; –; (66315). Elfdalian; diuor; n; (wild) animal; 0; –; –; (66292). English; deer; –; hoofed grazing or browsing animal of the family Cervidae, the males of which usually have deciduous branching antlers; 1; –; –; (66325). Faroese; dýr; n; animal; 0; –; –; (66288). German; Tier; n; (wild) animal; 0; –; –; (66296). Gothic; dius; n; (wild) animal; 0; –; –; (66340). Icelandic; dýr; n; animal; 0; –; –; (66284). Low German; dier; –; animal; 0; –; –; (66308).

Middle Dutch; dier; n; (wild) animal; 0; –; –; (66316). Middle English; deor; –; animal; deer; 0; –; –; (66326). Middle High German; tier; n; (wild) animal; 0; –; –; (66297). Middle Low German; dêr, dêrt; n; animal; 0; –; –; (66309). Norwegian (Bokmål); dyr; n; animal; 0; –; –; (66275). Norwegian (Bokmål); hjortedyr; n; deer (generic); 1; –; –; (66274). Norwegian (Nynorsk); dyr; n; animal; 0; –; –; (66280). Norwegian (Nynorsk); hjortedyr; n; deer (generic); 1; –; –; (66279). Old English; dēor; n; beast, esp. quadruped; wild animal; 0; –; –; (66327). Old Frisian; diār, diēr; n; (wild) animal; 0; –; –; (66337). Old High German; tior; n; (wild) animal; 0; –; –; (66298). Old Norse; dýr; n; wild animal; roe deer; 0; –; –; (66257). Old Saxon; dior; n; (wild) animal; 0; –; –; (66322). Old Swedish; diūr; n; animal; 0; –; –; (66260). Proto-Germanic; *deuza-; n; (wild) animal; 0; –; –; (66258). Swedish; djur; n; animal; 0; –; –; (66265). Swedish; hjortdjur; n; deer (generic); 1; –; –; (66264). Gr σεργοί ‘deer’ (uct. etym.) (66343) Classical Greek; σεργóς*; m; deer; 1; –; –; (66344). PIE *dhrono- ‘speckled, variegated’ (66365) Albanian (Tosk); drë; m; deer; 1; –; –; (66368). Classical Greek; αρανις; –; speckled; 0; –; –; (66366). Proto-Albanian; *drani-; –; –; 0; –; –; (66369). Proto-Indo-European; *dhrono-; –; speckled, many-coloured; 0; –; –; (66367). Skt hariṇá- ‘deer’ < hariṇá- ‘yellow’ (66371) Bengali; harin; –; deer; 1; –; –; (66374). Hindi; harin, hran, hiran, harnā, harinā, hirnā; m; deer; 1; –; –; (66373). Punjabi; harn, harnā; m; deer; 1; –; –; (66375). Sanskrit; hariṇá-; m; deer; 1; –; –; (66372). Skt mr̥gá- ‘wild animal, deer’ (66376) Hindi; mrig; m; deer; 1; –; –; (66378). Sanskrit; mr̥gá-; m; wild animal, deer; 3; –; –; (66377). Lat bēstia ‘beast, animal’ (uct. etym.) (66759) English; beast; –; animal; quadruped, bovine, beast of burden; brutal person; 0; –; –; (66798). Middle English; best, beest, beeste; –; animal; 0; Loan; Old French; (66799). Albanian (Tosk); bishë; n; beast, animal; 0; Loan; Latin; (66844).

Appendix 3b: Lexical data: Indo-European

Catalan; bèstia; f; animal; beast of burden; 0; –; –; (66841). Croatian; bèštija; f; beast; brutal person; 0; Loan; Italian; (66852). Czech; bestie; –; beast, animal; 0; Loan; Latin; (66846). Danish; bæst; n; animal, beast; 0; Loan; Middle Low German; (66765). Dutch; beest; n; beast, animal; 0; –; –; (66789). French; bête; f; animal; 0; –; –; (66825). French; biche; f; female deer; 1; –; –; (66822). German; Bestie; f; wild animal, predator; 0; –; –; (66780). Irish; péist; f; fabulous beast, reptile, monster; worm; 0; –; –; (66807). Italian; bestia; f; beast, animal; 0; Loan; Latin; (66818). Italian; biscia; f; (non-poisonous) snake; 0; –; –; (66820). Latin; bēstia; f; beast, animal; 0; –; –; (66764). Middle Dutch; beeste, beste; f,n; beast, animal; 0; Loan; Old French; (66790). Middle High German; bestia; f; beast, animal; 0; Loan; Latin; (66781). Middle Low German; bêst; n; beast; 0; Loan; Old French; (66761). Norwegian (Bokmål); beist; n; beast; dangerous wild animal; 0; Loan; Middle Low German; (66770). Norwegian (Nynorsk); beist; n; large wild animal; domestic animal, esp. of cattle; 0; Loan; Middle Low German; (66775). Old French; beste; f; beast, animal; 0; –; –; (66762). Old French; bisse; f; (wild) animal; female deer; 0; –; –; (66823). Old Irish; béist, biast; f; beast, monster; 0; Loan; Latin; (66811). Old Irish; péist, béist, biast, píast; f; beast, monster; 0; Loan; Latin; (66808). Polish; bestia; f; wild beast of prey; cruel, ferocious person; 0; Loan; Latin; (66848). Portuguese; bicho; m; animal; ferocious animal; insect; vermin; 0; –; –; (66836). Romanian; bestie; f; wild beast, ferocious beast; ferocious or cruel person; 0; Loan; Italian; (66838). Russian; béstija; –; beast, animal; 0; Loan; Latin; (66850). Scottish Gaelic; biast, bèist; f; beast; 0; –; –; (66810). Scottish Gaelic; pèist; f; beast, reptile; 0; –; –; (66813). Serbian; bèštija; f; beast; brutal person; 0; Loan; Italian; (66855). Spanish; bestia; f; beast; brutal person; 0; Loan; Latin; (66834). Swedish; best; c; beast; monster; 0; Loan; Middle Low German; (66760). Vulgar Latin; bestia; –; beast, animal; 0; –; –; (66763).

471

< PIE *stegh- ‘to prick, to sting’ (66858) English; stag; –; adult male deer, esp. one with a set of antlers; 3; –; –; (66886). Faroese; steggi; –; male (generic); male bird; 0; –; –; (66882). Icelandic; steggi; m; male bird; 0; –; –; (66877). Icelandic; steggr; m; male bird; tom-cat; 0; –; –; (66881). Latvian; stagars; –; stickleback; 0; –; –; (66898). Lithuanian; ste˜gė; f; stickleback; 0; –; –; (66899). Middle English; stagg, stagge, stag; –; male deer; male red deer, specifically at the fifth year; 3; –; –; (66887). Norwegian (Bokmål); stegg; m; male animal; male of certain birds; 0; –; –; (66869). Norwegian (Nynorsk); stegg; m; male animal; male of certain birds; 0; –; –; (66873). Old Danish; stag; –; barb, spike; 0; –; –; (66866). Old English; stagga, *stacga; n; male (red) deer; 3; –; –; (66888). Old Norse; steggi; m; male animal; 0; –; –; (66859). Proto-Germanic; *stagga-; –; –; 0; –; –; (66860). Proto-Indo-European; *stegh-; v; to prick, sting; 0; –; –; (66861). Swedish; stagg; c; stinging grass; 0; –; –; (66863). < PIE *rei-, *roi- ‘variegated, speckled’ (66900) Danish; rå; c; female roe deer; 3; –; –; (66928). Danish; rådyr; n; roe deer; 3; –; –; (66932). Dutch; ree; c; roe deer; 3; –; –; (66978). Dutch; rekke; c; female roe deer; 3; –; –; (67015). Elfdalian; rå-diuor; n; roe deer; 3; –; –; (66959). English; roe; –; small European and Asian deer, Capreolus capreolus; 3; –; –; (66988). Faroese; rá-djór; n; roe-deer; 3; –; –; (66955). German; Reh; n; roe deer; 3; –; –; (66963). German; Ricke; f; female roe deer; 3; –; –; (67009). Irish; riabhach; adj; speckled grey; dun, drab; 0; –; –; (67000). Latvian; ràibs; adj; dappled (especially of animals); 0; –; –; (66901). Lithuanian; raibas, rainas; adj; dappled, having brownish-yellow spots; 0; –; –; (66903). Low German; rikke; –; female roe deer; 3; –; –; (67012). Middle Dutch; rēa, ree; m,f; roe deer; 3; –; –; (66979). Middle English; roe; –; roe deer; 3; –; –; (66989). Middle High German; rēch, rē; n; roe deer; 3; –; –; (66964). Middle Low German; rē; n; roe deer; 3; –; –; (66975). Norwegian (Bokmål); rå; m,f; female roe deer; 3; –; –; (66937). Norwegian (Bokmål); rådyr; n; roe deer; 3; –; –; (66941). Norwegian (Nynorsk); rå; m,f; female roe deer; 3; –; –; (66946).

472

Appendix 3b: Lexical data: Indo-European

Norwegian (Nynorsk); rådyr; n; roe deer; 3; –; –; (66950). Old English; rā, rāha; m; roe deer; 3; –; –; (66990). Old High German; rēh, rēho; n,m; roe deer; 3; –; –; (66965). Old Irish; ríabach; adj; streaked, striped; of an indefinite dusky hue, swarthy; 0; –; –; (67001). Old Norse; rá; f; female roe deer; roe deer; 3; –; –; (66910). Old Prussian; roaban; adj; striped; 0; –; –; (66905). Old Saxon; rēho; m; roe deer; 3; –; –; (66985). Old Swedish; rā; f; roe deer; 3; –; –; (66913). Proto-Germanic; *raiha-, *raihan-; m; roe deer; 0; –; –; (66911). Proto-Germanic; *rikkī-; f; female roe deer; 0; –; –; (67010). Proto-Indo-European; *rei-, *roi-; –; variegated, speckled; 0; –; –; (66902). Sanskrit; riśya-; m; antelope; 3; –; –; (66907). Scottish Gaelic; riabhach; adj; brindled, grizzled; 0; –; –; (67003). Swedish; rå; c; roe deer; 3; –; –; (66917). Swedish; rådjur; n; roe deer; 3; –; –; (66922). PIE *bhrendh- (?) ‘horned animal, elk, deer’ (67250) Albanian (Tosk); bri; –; horn; horn, antlers; 0; –; –; (33865). Classical Greek; βρένδον; m,n?; deer, deerʼs head; 2; Loan; Messapian; (67251). < PIE *(H)uēnh₁-, *(H)unh₁- ‘to hunt, desire’ (67253) English; venison; –; the flesh of deer used as food; flesh of an animal killed in the chase or by hunting and used as food; 0; –; –; (67254). French; venaison; f; game (meat), specifically the meat of larger animals; 0; –; –; (67275). French; vener; v; to hunt; 0; –; –; (67283). French; vénerie; f; the art of hunting; 0; –; –; (67282). Italian; venagione; m; hunt, hunting; 0; –; –; (67269). Latin; vēnārī; v; to hunt; 0; –; –; (67258). Latin; vēnātiō; f; hunt, spoils of the hunt, game; 0; –; –; (67257). Latin; vēnātus; m; hunt; 0; –; –; (67295). Middle English; venaison; –; game (meat), specifically the meat of larger animals; 0; Loan; Old French; (67255). Old French; veneson, veneisun, venison, venoison; f; hunt, game; 0; Loan; Latin; (67256). Portuguese; veação; f; hunting; 0; –; –; (67307). Portuguese; veada; f; female deer (generic); 1; –; –; (67300). Portuguese; veado; m; deer (generic); venison; 1; –; –; (67301).

Proto-Indo-European; *(H)uēnh₁-, *(H)unh₁-; –; desire; 0; –; –; (67261). Proto-Italic; *wēnā-je/o-; v; to hunt; 0; –; –; (67259). Proto-Italic; *wēn-o/ā-; –; hunting; 0; –; –; (67260). Provençal; venaizo, venazo; –; ?; 0; –; –; (67319). Romanian; vânat; n; hunt; quarry; game, venison; 0; –; –; (67313). Spanish; venado; m; deer, venison; cuckold; 1; –; –; (67294). PGm *dajō(n)- ‘female animal, (fallow) deer’ (uct. etym.) (67329) Danish; då; c; female fallow deer; 4; Loan; Old English; (67336). Danish; dådyr; n; fallow deer; 3; –; –; (67338). Danish; dåhjort; c; fallow deer; 3; –; –; (67333). English; doe; –; female (fallow) deer; female hare or rabbit; 3; –; –; (67346). Faroese; dádýr; n; fallow deer; 1; –; –; (67345). Icelandic; dádýr; n; fallow deer; 1; –; –; (67344). Middle English; do, doo; –; female fallow deer; female hare or rabbit; 3; –; –; (67347). Norwegian (Bokmål); dåhjort; m; fallow deer; 4; Loan; Old English; (67340). Norwegian (Nynorsk); dåhjort; m; fallow deer; 4; Loan; Old English; (67342). Old English; dā; f; female fallow deer; 1; –; –; (67331). Old Swedish; dā; f; female fallow deer; 4; Loan; Old English; (67330). Swedish; dovhjort; c; fallow deer; 3; –; –; (67334). PCelt *kamŭsso, LLat gammus (uct. etym.) (67352) French; chamois; m; chamois, Rupicapra rupicapra; 3; –; –; (67359). German; Gämse; f; chamois; 3; –; –; (67353). Late Latin; gammus; m; deer; 1; –; –; (67365). Middle High German; gemeʒe; –; chamois; 3; –; –; (67354). Old French; camois; m; chamois; 4; Loan; ProtoCeltic; (67360). Old High German; gamiʒa; f; chamois; 1; –; –; (67355). Old Provençal; chamos; m; chamois; 4; Loan; Proto-Celtic; (67371). Portuguese; gama; f; female deer; 1; –; –; (67368). Portuguese; gamo; m; fallow deer; 3; –; –; (67366). Proto-Celtic; *kamŭsso-; –; chamois; 0; –; –; (67361). Spanish; gamo; m; deer (generic); 1; –; –; (67364). < PIE *bher- ‘to swell’ (67373) Latvian; briedis; m; deer, esp. fallow deer; stag; (formerly) elk; 1; –; –; (67374). Latvian; dambriedis; m; fallow deer; 3; –; –; (67378).

Appendix 3b: Lexical data: Indo-European

Lithuanian; bríedis; m; elk, moose; 3; –; –; (67383). Old Prussian; braydis; m; elk, moose; 3; –; –; (67387). Proto-Balto-Slavic; *breid-, *bried-; –; –; 0; –; –; (67375). Proto-Indo-European; *bher-; v; to swell; 0; –; –; (67377). Proto-Indo-European; *bhreydh-; –; –; 0; –; –; (67376). Pt corço, Sp corzo (uct. etym.) (67391) Portuguese; corça; f; female deer (generic); female roe deer; 1; –; –; (67394). Portuguese; corço; m; roe deer; 3; –; –; (67393). Spanish; corzo; m; roe deer; 3; –; –; (67392). PIE *yorḱ- ‘a kind of roebuck’ (67396) Breton; yourc’h; m; roe deer; 3; –; –; (67414). Classical Greek; δορκάς; f; a kind of deer, roe, gazelle; 3; –; –; (67400). Cornish; yorgh; f; roe deer; 3; –; –; (67426). Gaulish; íorkos; –; roebuck; 3; –; –; (67433). Latin; hircus; m; male goat; 0; –; –; (58557). Middle Breton; yourch; m; roe deer; 3; –; –; (67415). Middle High German; ireh; m; male goat; 0; –; –; (67437). Middle Welsh; iwrch; m; (male) roe deer; male goat (?); 3; –; –; (67408). Modern Greek; ζαρκάδι; n; roe deer; 3; –; –; (67399). Old Breton; iorch; –; goat (?), roe deer (?); 0; –; –; (67416). Old Cornish; yorch; –; goat (?), roe deer (?); 0; –; –; (67427). Old High German; irah, ireh, irh; m; male goat; 0; –; –; (67438). Proto-Celtic; *yorko-; –; roebuck; 0; –; –; (67409). Proto-Germanic; *irha-; m; he-goat; 0; –; –; (67439). Proto-Indo-European; *(H)yorko-; –; goat; 0; –; –; (67410). Proto-Indo-European; *iorḱ-; –; a kind of roebuck; 0; –; –; (67398). Welsh; iwrch; m; (male) roe deer; 3; –; –; (67407). PIE *h₃ewi-keh₂- ‘little sheep’ (67444) Old Cornish; euhig; f; female deer; 1; –; –; (67452). Old Welsh; eguic; –; female deer; 1; –; –; (67446). Proto-Celtic; *owīkā; –; hind, doe; 0; –; –; (67447). Proto-Indo-European; *h₃ewi-keh₂-; –; little sheep; 0; –; –; (67448). Sanskrit; avikā́-; f; ewe; 0; –; –; (67455). No etym. (–) Tocharian B; aineye*; –; black antelope; 4; Loan; Buddhist Hybrid Sanskrit; (94238). dog PIE *ḱuōn- ‘dog’ (60954) Albanian (Tosk); kuç; m; dog; 2; Loan; Slavic (branch); (61161).

473

Albanian (Tosk); qen; m; dog; 2; Loan; Romanian; (61041). Albanian (Tosk); shakë; f; dog, bitch; 2; Loan; Indo-Iranian (branch); (61057). Avestan; spaka-; –; dog-like; 0; –; –; (61073). Avestan; span-; m; dog; 1; –; –; (30040). Breton; ki; m; dog; 1; –; –; (26664). Bulgarian; kúče; n; dog; 1; –; –; (61169). Catalan; ca; m; dog; canid animal; 1; –; –; (61024). Classical Greek; κύων; m,f; dog; bitch; 1; –; –; (61039). Cornish; kei; m; dog; 1; –; –; (60983). Croatian; kȕče; n; dog, puppy; 1; –; –; (61165). Danish; hund; c; dog; 1; –; –; (25558). Dutch; hond; c; dog; 1; –; –; (25879). English; hound; –; hunting dog, esp. one able to track by scent; 1; –; –; (61142). Faroese; hundur; m; dog; 1; –; –; (25697). French; chien; m; dog; dog (generic); male dog; 1; –; –; (26921). French; chienne; f; bitch; 1; –; –; (61010). Gaulish; *cuno; –; dog; 1; –; –; (60991). Gaulish; Cuno-pennus; –; Dog-head; 0; –; –; (60990). German; Hund; m; dog; 1; –; –; (25767). Gothic; hunds; –; dog; 1; –; –; (26384). Hindi; sūnā; m; dog; 1; –; –; (28396). Hindi; sūnī; f; bitch; 1; –; –; (61083). Hittite; kuu̯an-; c; woman; 0; –; –; (43376). Icelandic; hundur; m; dog; 1; –; –; (25660). Irish; cú; f; dog, esp. greyhound, hunting dog; hero, champion; 1; –; –; (26420). Italian; cane; m; dog; 1; –; –; (26883). Latin; canīcula; f; bitch; 1; –; –; (61035). Latin; canis, canēs; m; dog; 1; –; –; (27538). Latvian; suns; m; dog; 1; –; –; (28080). Lithuanian; šuõ; m; dog; 1; –; –; (61065). Middle Breton; ci, qui; –; dog; 1; –; –; (26729). Middle Breton; quies; –; bitch; 1; –; –; (60980). Middle Dutch; hont, hond; m; dog; 1; –; –; (26318). Middle English; hound; –; dog, esp. hunting dog; 1; –; –; (26062). Middle High German; hunt; m; dog; 1; –; –; (26181). Middle Low German; hunt, hont; m; dog; 1; –; –; (26281). Middle Welsh; ki, ci; m; dog; 1; –; –; (26814). Modern Armenian; šun; –; dog; 1; –; –; (61055). Norwegian (Bokmål); hund; m; dog; 1; –; –; (25590). Norwegian (Nynorsk); hund; m; dog; 1; –; –; (25623). Occitan; canh, canha; m; dog; 1; –; –; (61002). Old Cornish; ci; –; dog; 1; –; –; (60984). Old English; hund, hunt; m; dog; 1; –; –; (26102). Old Frisian; hund; m; dog; 1; –; –; (26215). Old High German; hunt; m; dog; 1; –; –; (26143). Old Irish; cú; m,f,n; dog; 1; –; –; (26568). Old Norse; hundr; m; dog; 1; –; –; (26017).

474

Appendix 3b: Lexical data: Indo-European

Old Prussian; sunis; –; dog; 1; –; –; (28150). Old Saxon; hund; m; dog; 1; –; –; (26245). Old Swedish; hunder; –; dog; 1; –; –; (26352). Ossetian (Iron); kuydz; –; dog; 1; –; –; (61171). Persian; sæg; –; dog; 1; –; –; (30151). Portuguese; cão; m; dog; 1; –; –; (26999). Proto-Celtic; *kʷon-; –; dog; 0; –; –; (60957). Proto-Germanic; *hunda-; m; dog; 0; –; –; (61086). Proto-Indo-European; *ḱuōn-, *ḱuon-m, *ḱun-os; –; dog; 0; –; –; (60997). Proto-Indo-European; *ḱúwō(n)-; –; –; 0; –; –; (61050). Proto-Indo-European; *ḱwōn-, *ḱuwōn-; –; dog; 0; –; –; (60958). Proto-Indo-Iranian; *spaka-; –; dog; 0; –; –; (61058). Proto-Indo-Iranian; *spáka; –; –; 0; –; –; (61061). Proto-Italic; *kō, *kʷanem, *kunos; –; –; 0; –; –; (60996). Proto-South-Slavic; *kučę; n; dog, puppy; 0; –; –; (61162). Proto-Tocharian; *kuwu; –; –; 0; –; –; (61049). Provençal; can; m; dog; 1; –; –; (61028). Romanian; câine; m; dog; 1; –; –; (61020). Russian; sobáka; f; dog; 2; Loan; Indo-Iranian (branch); (27898). ́ f; bitch; 1; –; –; (61080). Sanskrit; śunī-; Sanskrit; śván-, śuna-; m; dog; 1; –; –; (28211). Sardinian; cane, cani; m; dog; 1; –; –; (27184). Scottish Gaelic; cù; m; dog; 1; –; –; (26476). Serbian; kȕče; n; dog, puppy; 1; –; –; (61167). Slovene; kužek; m; puppy; 3; –; –; (61163). Spanish; can; m; dog; 3; –; –; (61012). Swedish; hund; c; dog; 1; –; –; (25524). Tocharian A; ku; m; dog; 1; –; –; (30693). Tocharian B; ku; m; dog; 1; –; –; (30722). Welsh; ci; m; dog; 1; –; –; (26624). Pol, Ru suka ‘bitch’ (uct. etym.) (61176) Polish; suka; f; bitch; 1; –; –; (61177). Russian; súka; f; bitch; 1; –; –; (61178). Gr σκῠ́λᾰξ ‘dog’ (uct. etym.) (61179) Classical Greek; σκύλαξ, -αϰος; m,f; young dog, puppy; 3; –; –; (61181). Modern Greek; σκύλος; m; dog; 1; –; –; (61180). PSl *pь̀sъ ‘dog’ < PIE *peku- (?) (61183) Croatian; pȁs; m; dog; 1; –; –; (61192). Czech; pes; m; dog; 1; –; –; (27823). Old Church Slavonic; pьsъ; m; dog; 1; –; –; (61196). Polish; pies; m; dog; 1; –; –; (27861). Proto-Slavic; *pь̀sъ; m; dog; 0; –; –; (61185). Russian; pës; m; dog; 1; –; –; (61188). Serbian; pȁs; m; dog; 1; –; –; (61194). Slovene; pə̀s; m; dog; 1; –; –; (61190). ON rakki ‘dog’ (no etym.) (61198) Dutch; rekel; c; male dog; 1; –; –; (61217). Elfdalian; rakke; m; dog; 1; –; –; (25732). English; rake; v; (of a dog) to hunt by scent, with the nose to the ground; 0; –; –; (61218). Faroese; rakki; m; (young) dog; 3; –; –; (61212).

Icelandic; rakki; m; dog; 1; –; –; (61210). Middle Low German; rekel; m; large farm dog; 3; –; –; (61216). Norwegian (Bokmål); rakke; m; dog; white fox; 1; –; –; (61205). Norwegian (Nynorsk); melrakke; m; w