Cognitive Modeling and Verbal Semantics: A Representational Framework Based on UML 9783110909623, 9783110179514

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Cognitive Modeling and Verbal Semantics

W G DE

Trends in Linguistics Studies and Monographs 154

Editors Walter Bisang

(main editor for this volume)

Hans Henrich Hock Werner Winter

Mouton de Gruyter Berlin · New York

Cognitive Modeling and Verbal Semantics A Representational Framework Based on UML by

Andrea C. Schalley

Mouton de Gruyter Berlin · New York

Mouton de Gruyter (formerly Mouton, The Hague) is a Division of Walter de Gruyter GmbH & Co. KG, Berlin.

Printed on acid-free paper which falls within the guidelines of the ANSI to ensure permanence and durability.

ISBN 3-11-017951-2 Bibliographic information published by Die Deutsche Bibliothek Die Deutsche Bibliothek lists this publication in the Deutsche Nationalbibliografie; detailed bibliographic data is available in the Internet at . © Copyright 2004 by Walter de Gruyter GmbH & Co. KG, D-10785 Berlin All rights reserved, including those of translation into foreign languages. No part of this book may be reproduced or transmitted in any form or by any means, electronic or mechanical, including photocopy, recording or any information storage and retrieval system, without permission in writing from the publisher. Cover design: Christopher Schneider, Berlin. Printed in Germany.

To my parents and to Alex

"The question is", said Alice, "whether you can make words mean so many different things." "The question is", said Humpty Dumpty, "which is to be master - that's all." Alice was too much puzzled to say anything; so after a minute Humpty Dumpty began again. "They've a temper, some of them - particularly verbs: they're the proudest - adjectives you can do anything with, but not verbs - however, / can manage the whole lot of them!" (Lewis Carroll, Through the Looking Glass)

Preface Humpty Dumpty would be a very lucky and much sought-after guy if his claim as expressed in the quote above also held from a linguistic semantic point of view, namely, that he "can manage the whole lot" of the verbs. Indeed, those linguists who are in search of a method for grasping and representing the semantics of verbs would keep demanding for his secret formula. Unfortunately, there is no way to ask him whether his claim also covers this linguistic desideratum, which has been in the focus of linguists for quite some time and probably will remain. To date it is not possible to model the semantics of verbs adequately. This work is another attempt to promote and bring forward research in this area and to proceed towards the goal Humpty Dumpty might have reached - although he most probably has not, in particular if we take his 'reliability' into account. The approach to be introduced here results from a dissatisfaction with the approaches that have been proposed to date. In particular, the aim was to find an intuitive but nonetheless formal access to verbal semantics. Since most approaches are either intuitive or formal, we will try to merge several theoretical insights into one model, the Unified Eventity Representation (UER). One obvious innovation is the introduction of object-orientation as a new paradigm to linguistic semantics. Another is the proposed graphical representation. It is well-known that grammarians work with tree-structures, knowledge representation approaches use graphs, and modeling languages in computer science employ richly structured graphical languages - such as the Unified Modeling Language (UML) the UER is based on. Nevertheless, though e.g., semantic maps and networks are applied in linguistic semantics, it has not been tried to apply a graphical structure as rich as the UML to model the internal structure of verbal semantics in linguistics. Specifically, we believe that an approach using a mixture of graphical elements as well as linear textual constructs is very promising. Graphical elements in general express structure, whereas the linear constructs mostly name contents, i.e., properties and characteristics which are co-conceptualized with the graphical elements. A representational framework usable on different levels of granularity, and thus the possibility to refine one's model as far as is sensible in the scope of investigation, will hopefully help progress in linguistic semantics.

viii

Preface

The present investigation is my dissertation for the Ludwig-MaximiliansUniversität München, Germany, in a slightly revised format for book publication. Apart from a rework to improve readability, Section 7.5. and Chapter 8. have been added to discuss the extension potential of the UER with regard to compositional semantics, and to demonstrate the relevance of the UER for linguistic theory building in an additional application of the framework. First and foremost, I wish to thank my supervisors Dietmar Zaefferer and Leila Behrens. Dietmar Zaefferer has my sincere gratitude for his constant support during the last years, for his never-ending interest with which he followed my research - and for his constructive remarks on both analysis and underlying framework. I am grateful to Leila Behrens for her insightful comments and for substantial discussions which helped to improve the manuscript considerably. Many thanks are also directed to Alexander Knapp for the indispensable, stimulating discussions from which I benefited greatly while seeking the most sensible extension of the UML. I very much appreciate the financial support of the Deutsche Forschungsgemeinschaft (DFG) I was happy to receive as a member of the graduate program "Sprache, Information, Logik". Moreover, I would like to thank the University of New England, Australia, for supporting the finalization of the book. I am grateful to Dennis Alexander, Patric Bach, Brett Baker, Georg Borner, Shirley Cooke, Simona Fina, Helen Fräser, Cliff Goddard, Catherine Jukes, Eleni Kriempardis, Marilyn Miller, Veronica O'Reilly, Cindy Schneider, Meike Tewes, and Simone Welten for proof-reading and commenting on portions of the manuscript. All remaining errors are, of course, my own responsibility. Furthermore, I would like to thank Christiane Hofbauer for our lively discussions and Julia Blaschke for her technical support. Many, many thanks go to all my friends who supported me to stay the course. However, I would like to pass my sincerest thanks to Alexander Borkowski, to whom I am very much indebted. He not only lent me his ears whenever there was a technical problem and proof-read the manuscript. In addition, he discussed the UML and the UER with me in uncountable hours, thereby helping me to improve many of the concepts presented in this work. As my place of refuge, he always managed to get me back to work and encouraged me to go on when my motivation flagged. Last but not least, I would like to thank my parents - for supporting me for such a long time and being so patient with me. Armidale, April 2004

Andrea C. Schalley

Contents

Preface List of List of tables

vii xiii xviii

figures

1.

Introduction

1

2. 2.1. 2.1.1. 2.1.2. 2.1.2.1. 2.1.2.2. 2.1.3. 2.1.3.1. 2.1.3.2. 2.2. 2.2.1. 2.2.2. 2.2.3. 2.2.4. 2.2.5. 2.3.

Survey of research positions Lexical semantics of verbs Approaches to lexical semantics Internal structures Semantic roles and protoroles Aktionsart and verb classification Structural relations Sense relations and lexical fields Polysemy Approaches to decompositional semantics Generative Semantics Jackendoff 's Conceptual Semantics Fillmore's Frame Semantics Wunderlich's Lexical Decomposition Grammar Pustejovsky's Generative Lexicon Semantic primitives and the Natural Semantic Metalanguage

10 11 12 16 16 22 26 27 31 34 36 40 49 55 58 68

3. 3.1. 3.2. 3.3. 3.4.

Introducing the UER A rigorous cognitive approach towards verbal semantics Foundation of the UER General characteristics Diagram elements

75 75 80 81 83

4. 4.1. 4.1.1. 4.1.2. 4.1.3.

Basic concepts of the UER General extension mechanisms Constraint Comment Property

. .

87 88 88 90 90

χ

Contents

4.1.4. 4.1.5. 4.2. 4.2.1. 4.2.2. 4.2.3. 4.2.4. 4.2.5. 4.2.6. 4.2.7. 4.2.8. 4.2.9. 4.2.10. 4.2.11. 4.2.12. 4.3. 4.3.1. 4.3.2. 4.3.3. 4.3.4. 4.3.5. 4.3.6. 4.3.7. 4.3.8. 4.3.9. 4.3.10.

Stereotype Enumeration Static structure concepts Class Attribute Object Association Association end Multiplicity Qualifier Link Association class Generalization Dependency Derived element Dynamic structure concepts State Passive simple state (PSS) Active simple state (ASS) Composite state Submachine state Pseudostates Final state Event Guard Swimlane

92 94 95 96 98 99 101 103 105 106 107 108 110 112 114 114 115 119 120 121 124 126 129 129 133 134

5. 5.1. 5.1.1. 5.1.2. 5.1.3. 5.2. 5.2.1. 5.2.2. 5.2.3. 5.2.4. 5.3.

Advanced concepts of the UER Aggregation Meronomy Attachment Possession Transition Simple transition Complex transition Transitions to and from composite states Factored transition paths Blackbox .

136 136 140 144 146 147 147 153 154 156 158

Contents

xi

5.3.1. 5.3.2. 5.4. 5.4.1. 5.4.2. 5.4.3. 5.4.4. 5.5. 5.5.1. 5.5.2. 5.5.3. 5.6.

Stubbed transition Stubbed signal Eventity frame Dynamic core and static periphery Participant class Participate association Omittance of elements Template Template parameter Binding Unspecified binding Subcore state

159 160 161 163 165 167 168 169 172 172 177 178

6. 6.1. 6.2. 6.3. 6.4. 6.5. 6.6. 6.7. 6.8. 6.9. 6.10. 6.11. 6.12. 6.13. 6.14. 6.15. 6.16.

Interpretation of UER concepts Eventity frames: Central cognitive units Enumerations: Recurring cognitive categories Attributes: Semantic features Classes: Categories Participant types: Referencing ontological categories . . Participant roles: Referencing prototypical semantic roles Associations / aggregations: Participant relationships . . Generalizations: Inheritance relationships Simple states / transitions: Basic eventity types Events / cause-signal: Triggers and causation Submachine / subcore states: Conceptual structuring . . Templates: Linguistic description device Stereotypes: Clusters of recurring characteristics Properties: Semantic specifications Constraints: Semantic restrictions Unspecified elements: Underspecification

181 183 185 189 193 195 200 206 209 210 213 219 222 224 227 230 231

7. 7.1. 7.2. 7.3. 7.4. 7.5.

General issues Constraints for representing verbal semantics Static vs. dynamic aspects of verbal semantics Modeling granularity Semantic primitives Towards a compositional semantics

.. . . . .

..

233 235 237 238 241 244

xii

Contents

8. 8.1. 8.2. 8.3. 8.4.

Application I: Eventity classification States: States, acts, and activities Transitions: Change eventides Cause-signals: Interactional eventides Overview and outlook

251 253 257 267 276

9. 9.1. 9.1.1. 9.1.2. 9.2. 9.2.1. 9.2.2. 9.3. 9.3.1. 9.3.2. 9.3.3. 9.4. 9.4.1. 9.4.2. 9.4.3. 9.5.

Application II: The polysemy of German setzen English put and German verbs of position The PUT eventity Verbs of position and their causative counterparts The prototypical reading of setzen Caused vs. induced movement Conception of the actor's control Prototypical reflexivity The UER representation of the reflexive variant Renunciation of the locational specification Review of prototypical readings Extensions of the prototypical case Loss of the posture specification: Pure localization Loss of the agent: Settling Focusing the action: Traversing Recapitulation of results

281 282 282 287 289 290 293 294 296 298 302 303 304 312 315 322

10.

Epilog

326

A. A. 1. A.2. A.3. A.4. A.5.

The notational elements of the UER General extension mechanisms Static structure elements Dynamic structure elements Eventity frame and eventity frame template Miscellaneous

329 329 336 342 350 351

Notes References Index of names UER index Subject index

353 383 413 419 435

List of figures

1 2 3 4

Semantic representation of χ killed y (McCawley) Deriving the surface structure for χ killed y (McCawley) . . . . Example of event decomposition (Pustejovsky) Basic event types (Pustejovsky)

37 38 62 63

5 6 7 8

Introductory example (part 1) Introductory example (part 2) NOTE Type-instance dichotomy

76 78 85 86

9

CONSTRAINTS

90

10 11

Varieties of STEREOTYPE notation Notational form for declaring STEREOTYPES

93 94

12 13

ENUMERATION CLASS

95 97

14 15 16 17 18 19 20

STEREOTYPES applied to groups of list elements OBJECT (with flow relationship) Binary ASSOCIATION N-ary ASSOCIATION Various adornments on ASSOCIATION ends Qualified ASSOCIATION LINKS

97 100 102 103 105 107 108

21 22 23 24

ASSOCIATION CLASS GENERALIZATION DEPENDENCY STATE

109 112 114 118

25

Internal TRANSITION

118

26

PASSIVE SIMPLE STATE

120

27 28 29 30 31 32

ACTIVE SIMPLE STATE variants COMPOSITE STATE with concurrent regions COMPOSITE STATE with sequential subSTATES SUBMACHINE STATE with non-default exits Decision Symbols for SIGNAL sending and receipt

121 123 124 125 128 132

xiv

List of figures

33 34

SIGNAL sending with unspecified sending time SWIMLANE

133 134

35

AGGREGATION

139

36 37 38

MERONOMY ATTACHMENT POSSESSION

144 145 147

39 40 41 42 43 44 45 46 47 48 49

Simple TRANSITION Gradual TRANSITION Interrupted gradual TRANSITION Unspecified source STATE Unspecified target STATE Complex TRANSITION History indicator Junction point Choice point Stubbed TRANSITIONS Stubbed SIGNALS

149 151 151 152 152 153 156 158 158 160 161

50

EVENTITY FRAME

163

51

General outline of EVENTITY FRAME

164

52 53 54

PARTICIPANT CLASS PARTICIPATE ASSOCIATION EVENTITY FRAME TEMPLATE

167 168 171

55 56 57 58

Multiple binding Bound element (total binding) Partial binding Unspecified binding

174 175 177 178

59

SUBCORE STATE

180

60 61 62 63 64 65 66 67 68

Reading of sit and instance ENUMERATION Dimension ENUMERATION Velocity DegreeOf Coincidence and DegreeOf Remove Example of PARTICIPANT CLASS'S ATTRIBUTE compartment. Participant ontology Agent and effector roles TAKE-eventity UER metamodel inheritance structure for STATES

183 186 187 188 193 197 205 207 213

List of figures XV

69 70 71 72 73

WECKEN-and WACHKÜSSEN-eventities 217 KILL-and CAUSE-eventities 218 FETCH-eventity using a SUBMACHINE STATE (problematic) . 220 FETCH-eventity using a SUBCORE STATE 221 Representation of the undergoer of RAIN 228

74

Variants of representing the dynamic structure of FETCH . . . 238

75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93

Experiencer eventities States Actions Activities Acts General change Achievements Ingressives Alteratives and inchoatives Terminatives Egressives Desitives and conclusives General causation Causatives Continuous causatives Deducives Factives Resultatives Expulsives

252 253 255 255 256 257 260 261 262 263 264 265 268 269 271 271 273 274 275

94 95 96 97 98 99 100 101 102 103

PUT-eventity LOCALIZED-eventity SITZEN-eventity SETZEN-eventity Instantiated SETZEN-eventity Prototypical SICH_SETZEN-eventity SICH_SETZEN-eventity (with unspecified location) PUT-eventity (with unspecified location) SETTLE-eventity TRAVERSE-eventity

283 285 288 288 293 297 301 312 314 319

xvi

List of figures

104 105 106

LEAP and CROSS with their abstract parent TRAVERSE . . . 320 MEREJJEAP-eventity 321 Overview of the discussed readings of setzen 323

107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140

ENUMERATION notation 330 AGGREGATION notation 336 Varieties of ASSOCIATION notation 337 ASSOCIATION CLASS notation 338 ASSOCIATION end adornments 339 Bound element notation 340 CLASS notation 340 CLASS TEMPLATE notation 341 DEPENDENCY notation 341 GENERALIZATION notation 341 LINK notation 341 Varieties of OBJECT notation 342 QUALIFIER notation 342 Variants of ACTIVE SIMPLE STATE notation 343 BLACK BOX notation 343 Complex TRANSITION notation 344 Notation of COMPOSITE STATE with concurrent regions . . . . 344 Notation of COMPOSITE STATE with sequential subSTATES . . 344 Gradual TRANSITION notation 345 Notation of initial PSEUDOSTATE and final STATE 345 Internal TRANSITION notation 345 PASSIVE SIMPLE STATE notation 346 Choice PSEUDOSTATE notation 346 Create PSEUDOSTATE notation 346 Decision notation 346 Destroy PSEUDOSTATE notation 347 Fork notation 347 History PSEUDOSTATES notation (history indicators) 347 Gradual PSEUDOSTATE notation 347 Join notation 347 Junction PSEUDOSTATE notation 347 Notation of SIGNAL sending with unspecified sending time . . 348 Simple TRANSITION notation 348 SUBMACHINE STATE notation (with stub STATES) 348

List of figures xvii 141 142 143 144 145 146 147 148

SUBCORE STATE notation SWIMLANE notation Unspecified Source STATE notation Unspecified Target STATE notation EVENTITY FRAME notation EVENTITY FRAME TEMPLATE notation PARTICIPANT CLASS notation NOTE notation

349 349 349 349 350 350 350 351

List of tables

1 2 3 4

Van Valin and LaPolla's list of semantic roles The four Vendler classes Frame elements of the Commercial Transaction Frame Semantic primes of the NSM

5

Predefined kinds of DEPENDENCY

113

6

Secondary characteristics of MERONOM Υ

141

7 8

Change eventity classes Overview of eventity classes

266 276

9 10 11

List of predefined CONSTRAINTS List of predefined PROPERTIES List of predefined STEREOTYPES and keywords

329 330 333

....

18 25 52 70

Chapter 1. Introduction To date, rigorous approaches to the representation of verbal semantics, and lexical semantics in general, have not put much effort into achieving cognitive adequacy for their frameworks. This book sets out to take a major step in this direction. It develops a representational framework for verbal semantics that is formal and intuitive at the same time. This means in effect proposing a framework that is in principle computer processable on the one hand, and yet on the other hand whose representations reflect the wealth and flexibility of natural language in an intuitively plausible way and in accordance with our current knowledge about natural language. A new decompositional framework for the modeling and description of verbal semantics is proposed, the Unified Eventity Representation (UER). The development of the framework is based on results from linguistics, psychology, and computer science. In particular, the UER framework adopts and adapts the current lingua franca for the design of object-oriented systems in computer science, the Unified Modeling Language (UML). In contrast to other formal approaches to lexical semantics, it is neither logical nor functional in nature, but uses a third paradigm found in programming languages: object-orientation is introduced as a new paradigm to linguistic semantics. Thereby, a new route to the formal treatment of verbal semantics is opened up. The overall design of the UER allows us to tackle in one framework different traditional semantic problems that have to date often been treated separately, such as polysemy (including systematic polysemy), sense relations, lexical fields, underspecification, default interpretations, and complex event structures, to mention a few. Our approach is a cognitive one - we understand the meaning of verbs to be conceivable as concepts of events and similar entities in the mind. These concepts (including abstract entities such as propositions) have to be represented appropriately. We will refer to them as eventities (cf. Zaefferer 2002a) in this investigation. Following this cognitive approach, a development of a new framework for the representation of verbal semantics results in the development of a framework for the representation of eventities in general. That is, our aim is to be able to represent conceptual elements that are not necessarily bound to lexicalizations, but which constitute cognitive units

2

Introduction

(cf. also Avrahami and Kareev 1994:245). Examples of eventities are PUT or FETCH, which are lexicalized in English, as the instantiations in (1) show: (1) a. She put the books on the table. b. She fetched juice from the fridge. Eventities are, roughly speaking, entities which represent phenomena that run within time. Their counterparts in ontological terms are ineventities, entities which typically occur as participants in eventities. (For a more detailed discussion of the terms eventity and ineventity, cf. Section 6.5.) Strictly speaking, the term 'eventity' is used to refer to the concepts or generic entities (which are rendered in capitals such as PUT or FETCH) and not to instances, i.e. instantiations or occurrences of these as in (1). However, when the meaning is clear from the context and obvious in the rendering, the term is also used to refer to instances in some cases. To date, many representations of verbal semantics within more formal approaches, such as those using predicate logic, include place-holders for participants of the eventity and list the semantic roles of the participants, if present. Participants are referred to by variables, such as x, y, and z as in Example (2), whereas semantic roles are represented by two-place predicates such as Agent, Theme, and Goal. In the simple example in (2), the one-place predicate Put representing the the eventity PUT predicates over the event variable e which is a place-holder for instances of the eventity.l (2) jc puts y on/in/next to/... z Put(e) AAgent(e,x) ATheme(e,y) AGoal(e,z) In yet other frameworks, a decompositional structure for PUT such as (3) may indicate the course of events (in recent approaches also possibly containing temporal information).

(3) Cause(x,Become(Located(y,z))) However, in (2) no structural difference is made between the variables for participants and the event variable in the formalism, and roles and eventities differ only in the number of arguments they take. In (3), the position relation between the theme and the goal is not specified at all. Rather seldom, selectional restrictions applying to participants of an eventity (e.g., an entity can only sit down if it has the disposition of taking a sitting posture) are depicted

Introduction

3

in formal approaches to lexical semantics. Other factors could also be discussed, such as the representation of causation, or how different Aktionsarten are to be captured appropriately. Yet, we will not follow this tradition, because we consider well-elaborated representations of verbal semantics using predicate logic to be rather unintuitive, due in parts to the sentential and thus sequential representational form.2 Sentential representations are sequential, like the propositions in a text. Diagrammatic representations are indexed by location in a plane. Diagrammatic representations also typically display information that is only implicit in sentential representations and that therefore has to be computed, sometimes at great cost, to make it explicit for use. (Larkin and Simon 1987:65)

The UER expresses its descriptions and representations in diagrams, using a mixture of graphical elements as well as linear textual constructs. Diagrams allow verbal semantics to be modeled in an intuitive way. Different conceptual elements are expressed using different representational elements. Structural components are combined visually in a way that iconically represents the way in which they are conceptually combined. This exploitation of the two-dimensional graphical representation increases the degree of intuitiveness. The UER is precisely grounded, in that the syntax and semantics of its modeling elements are explicitly specified. In other words, representations of verbal semantics within the UER are backed up by a metalanguage which guarantees that the semantic building blocks of the representations are placed into structured, semantically defined surroundings and which explicates how they can be combined in a well-defined way and have to be interpreted. As indicated above, the UER is based on the Unified Modeling Language (UML). Consequently, the UER adapts the object-orientation from the UML. Roughly speaking, object-oriented systems represent entities together that conceptually 'belong together' - components of representations are arranged as they are arranged conceptually. Thus the foundational concept of the UER is the object, or, put differently, the particular entity Out there in the world' that possesses a definite identity and specific characteristics describing its current state. The modeling of eventities using the object-oriented approach highlights states and actions of these entities as well as their interactions. In other words, it centers around how we conceptualize the course of events or the eventities in which entities participate. This corresponds to verbal semantics including a static and a dynamic aspect: the static one is concerned with

4

Introduction

the participating objects, and the dynamic one is concerned with the course of events. Due to the object-orientation, this distinction of static vs. dynamic is explicitly elaborated in the UER. The UER is a unified representational framework in two ways. First, it is based on the UML which itself is unified in that it merges the results of several years of research and of several different approaches towards an appropriate graphical modeling language in computer science. Secondly, diverging aspects of linguistic semantics research are unified in the UER, as will become obvious in the course of this investigation. There are some basic criteria that have to be met in order to obtain a powerful modeling language for verbal semantics. Although we will not claim that the UER in its present state of development already fulfills all those criteria, they are the criteria along the lines of which the framework is being developed. These criteria are (cf. also Helbig 2001:6-8 and Jackendoff 1983:11): - Expressiveness There should not be an eventity that cannot be represented. The framework has to permit distinct representations for distinct eventities and verb meanings. - Universality "In order to account for the fact that languages are (largely) intertranslatable, the stock of semantic structures available to be used by particular languages must be universal" (Jackendoff 1983:11). In other words, the modeling elements (i.e., the constructs of the UER) provided within the UER framework have to enable users to account for all phenomena that occur within verbal semantics, regardless of the language. - Cognitive adequacy The modeling elements should license the modeling of conceptual structures and their manifestations in the semantics of verbs. The models have to feature conceptual centrality, i.e., a specific representation has to exist for each concept. In computer science, this requirement has led to the demand for object-orientation (cf. above). Another requirement mentioned by Helbig will not be considered so important in the UER. That is practicability: every system of modeling elements designed for fruitful application has to meet practical requirements. As such, he mentions that it has to be technically manageable and implementations need to be effective (Helbig 2001:7). Although the UER as an adaptation of the UML presumably fulfills the requirement of practicability because of its proximity to the UML, this has not been worked out to date. Our focus rests on the development of a representational framework for verbal semantics and

Introduction

5

thus on the theoretical linguistic perspective. Requirements such as practicability are kept in view, but are on no account indispensable. That is, if we have to decide between practicability in the above sense and theoretical linguistic adequacy, the latter will be preferred. In order gain an overview of the different positions held in the literature, a survey of research positions is given in Chapter 2. The chapter begins with a brief general treatment of lexical semantics, and then narrows down the focus to verbal semantics. Semantic roles, proto- and macroroles, Aktionsart and verb classification, sense relations, lexical fields, and polysemy are discussed. The heart of this review, however, is the treatment of positions of lexical decomposition in Section 2.2. Five approaches towards decomposition are presented in detail: Generative Semantics, Jackendoff's Conceptual Semantics, Fillmore's Frame Semantics, Wunderlich's Decomposition Grammar, and Pustejovsky's Generative Lexicon. Each time, it is indicated what aspects are relevant for the development of the UER, which arguments are rejected, and which ones are adopted for the UER. The survey serves as an outline of the state of the art and builds the linguistic foundation from which we start the presentation of the UER. In particular, it comprises a description of several linguistic aspects that play an important role in the design of the UER. In order to show where particular aspects are expressed in the UER, many cross-references to the following chapters are included. Chapters 3., 4., and 5. present a formal specification of the UER in three steps: they offer the foundation, the basic concepts, and the advanced concepts of the UER. No background knowledge of the UML is required, as all constructs of the UER- new, adapted and adopted ones - are introduced and their semantics and syntax are described in detail. In addition, for most of the introduced concepts an example is briefly discussed, and the respective concept's intended relevance for linguistic modeling is indicated. UER concepts are not commented on in these chapters, because the chapters are intended to serve as a reference guide enabling users to quickly gain an overview of each concept. (This is supplemented by Appendix A., which lists the notational elements of the UER and gives their general pattern in the form of a diagram element or their default syntax.) As the Chapters 4. and 5. are presented in a formal way, it might be tedious to read them thoroughly at the beginning. Therefore, we recommend not to go too deep into details in a first reading, but to try to catch an idea of the concepts and then move on. The foundation of the UER from the computational side, the UML, is too extensive to be explicated in detail. However, Chapter 3. describes the

6

Introduction

UER's overall proximity to the UML and the common ground of the two frameworks. This common ground includes the UML's four-layer architecture that is adopted for the UER. Moreover, the basics of the diagrams and modeling elements of the UML apply to the UER in the same way: in both, three kinds of visual relationships (connections, containments, and visual attachments) and four kinds of graphical constructs (icons, two-dimensional symbols, strings, and paths) are important. Other constructs that are deployed in the specification of the modeling elements, and are thus underlying constructs, are also introduced in Chapter 3. Finally, the type-instance dichotomy that is featured in the UML is carried over to the UER, because it reflects a cognitive distinction of particular importance in linguistics that has been touched on above. The aim in the modeling of verbal semantics is to represent distinct readings of verbs, and hence generic descriptions of meaning. This is clearly distinguished from the representation of an actual utterance, in which the verb is instantiated as a token. Thus, a verb meaning is a concept, i.e. an eventity type, whereas a verb token refers to an eventity instance. This difference of generic description vs. instance corresponds to the type-instance dichotomy, which is graphically well supported by the UML and accordingly by the UER. Chapter 4. specifies the basic concepts of the UER. The three sections of this chapter list general extension mechanisms, static structure concepts, and dynamic structure concepts. The split into static structure and dynamic structure concepts reflects the distinction of static and dynamic aspects of verbal semantics. Much of the specification presented for the different concepts is adopted from the specification of the respective UML concepts. This is precisely documented by the references to the UML Specification Version 1.4. Divergences from the UML specification are also made explicit, as some concepts are adjusted to the linguistic purpose of the UER. The last technical chapter is Chapter 5., which introduces advanced concepts of the UER. These are concepts that have been developed to meet the requirements of our linguistic application domain, i.e. the chapter contains several UER-specific concepts. Moreover, we consider concepts which, though adopted from the UML, have undergone changes in order to adjust them to the UER's purpose. An interesting point of this chapter is the AGGREGATION concept with its descriptive fine-graininess. However, of central importance for the current purpose of the UER is the EVENTITY FRAME concept, because it represents the conceptual unit 'eventity' the UER focuses on.

Introduction

7

Chapter 6. delivers an interpretation of UER concepts in terms of their cognitive adequacy and elaborates on their linguistic relevance. The chapter integrates insights from artificial intelligence, psychology, and typological, cognitive, and theoretical linguistics. For the most important UER concepts the question of why they have been designed the way they have is answered. In addition, some sets which are necessary for the application of the UER in lexical semantics are itemized (without defining them comprehensively, as final developments are subject to further typological research). Amongst other issues, a tentative participant ontology is developed (which includes, unlike previous approaches, eventities as potential participants). As well, our approach towards semantic roles is indicated, and the UER's basic dynamic structuring is shown to take conceptual considerations and Aktionsart differences into account. Chapter 7. closes the description of the UER by discussing general issues. It touches on the question of general constraints for representing verbal semantics, the relationship between static and dynamic aspects of verbal semantics, questions of modeling granularity, the notion of semantic primitives, and what an extension of the UER towards compositional semantics could look like. Similar to the UML, the UER is currently designed as a very permissive system. That is, although particular representations are in principle correct in terms of the UER specification, a lexicalization of these conceptualizations will probably not occur in natural languages. In this sense, the UER could be considered to Overgenerate'. However, the UER has intentionally been designed so broadly, in order to allow, e.g., for investigations into the potential complexity of lexicalized eventity concepts, and into which representational components depend on one another and need to occur simultaneously. Results of such studies can easily be included in the UER as well-formedness rules or general constraints for representing verbal semantics. Examples are given in the first section of Chapter 7. Another intriguing point of discussion concerns modeling granularity. The UER allows its users to adjust the granularity of the modelings with respect to the application domain and the investigational depth of the respective studies. Eventities or verbal meanings can be represented with different degrees of elaboration. In other words, with the UER we decidedly turn away from the expectation that there are 'absolute' semantic descriptions or representations. This turning away finds expression in the two applications in Chapters 8. and 9., whose models are driven by the foci and aims of the respective studies. The applications give an idea of the general broad applicability and power of

8

Introduction

the UER and the different investigational approaches and domains the UER can support. In the first application, set forth in Chapter 8., an eventity classification is developed. We follow a 'generative' approach and use the UER as a tool to systematically discuss different well-formed UER structures and their linguistic relevance. This allows us to develop hypotheses as to what is conceptually possible, and to systematically link conceptual structures to linguistic coding. Since the classification is put forward in terms of different dynamic structures, Aktionsart distinctions are reflected. The second application, Chapter 9., is more hands-on. It discusses the polysemy of the German causative verb of position setzen (roughly translatable as 'sit, sit down, put, settle, leap'). The study is based on actual language data: the examples have been extracted from the COSMAS I corpus of the Institut für Deutsche Sprache (IDS) Mannheim. Starting from the representation of the prototypical readings of setzen, six other readings are represented. In the course of the chapter, the structural correlations between the readings are precisely specified by means of the UER. Interestingly, although similarities between directly related readings are obvious when comparing their graphical representations, an overall comparison shows that no modeling element remains unaltered throughout the representations (cf. Wittgenstein's notion of family resemblance). To conclude, we will briefly comment on the notational conventions. Important UER terms are henceforth rendered in small capitals in order to distinguish them from linguistic terminology, as for example the UER term 'EVENT' in contrast to the linguistic notion of 'event'. Eventides such as 'SIT' are represented in capitals, as are non-structural predicates such as 'ALIVE' in the survey in Chapter 2. Other newly defined terms are displayed in italics, as for example 'determiner', examples from natural languages such as 'setzen' (with translations in simple quotation marks), and emphasis. As it was not possible to do without anticipations - in particular in Chapters 4. and 5. where the UER constructs are introduced - we have taken care to include cross-references within the manuscript and provide extensive indexes at the end. Apart from the Index of names, a UER index has been separated from the Subject index in order to avoid terminological confusion between UER and linguistic terms, and to facilitate the locating of UER elements in the text. In the Index of names, page numbers in italics refer to the References section. Authors listed in the index with merely italic page numbers are not explicitly named in the manuscript. This can be for one of the following

Introduction

9

reasons: (i) they are authors of an article in a collection, where the whole collection was cited in the manuscript, but for the sake of explicitness the relevant articles are listed in the References section, (ii) they are co-authors of works with more than three authors (in such a case, only the first name is cited within the manuscript, but the References section displays all names), or (iii) they are editors of collections, out of which more than one article is cited (in such a case, the collection is listed as a separate entry in the References section). Bold page numbers in the UER index indicate the page on which the corresponding UER term is introduced and specified, italic page numbers indicate the listing of the entry in the 'notational library' in Appendix A.

Chapter 2. Survey of research positions

In this chapter, an overview of the most prominent linguistic research positions that are relevant for the UER is given. Since the aim of this book is to develop the representational framework UER, primarily aspects relevant for the UER will be treated in the presentation. The survey has been divided into different fields playing a role in the UER. This includes a survey of lexical semantics of verbs in general (Section 2.1.) and a treatment of decompositional semantics (Section 2.2.). Furthermore, the notion of semantic primitives is introduced and discussed from the perspective of the Natural Semantic Metalanguage (Section 2.3.). However, nothing will be said about reference and denotation. This is treated in, e.g., Frawley (1992) and Lyons (1977a). For a survey of the development of lexical semantics in general, cf. Langer (1996), and for reviews on theories in lexical semantics, cf. Levin (1985). Cf. also the articles of Cruse et al. (2002) listed in the bibliography and Stein (1999) for a treatment of different issues in lexical semantics. Moreover, we will not discuss models of knowledge representation as means for conceptual modeling, and we will also refrain from introducing the UML (though it lays the foundations of the framework presented in this work). The general characteristics of UML are listed in Chapter 3., in parallel with an introduction to the general characteristics of the UER. Readers interested in approaches of modeling and semantic representation within the fields of knowledge representation and artificial intelligence are, in particular, referred to the works of Burg and Riet (who employ a graphical language similar to the UML in their COLOR-X system), Helbig (who uses semantic nets, the so-called MultiNets), Schank (who works with linked networks of concepts in his Conceptual Dependency Theory), Sowa (employing his Conceptual Graphs mechanism), and Wilks (working within his Preference Semantics).3 Although it would be interesting to compare these approaches to the UER, unfortunately it is beyond the scope of this work.

Lexical semantics of verbs

2.1.

11

Lexical semantics of verbs

Lexical semantics of verbs - understood as the investigation of meaning as expressed by elements of a particular class in the lexicon, namely verbs (including serial verb constructions and other phrasal verbs, but not verb phrases as such) - is the study of meaning of those elements. Syntax, morphology, and pragmatics are, in general, disregarded. The task of deciding which lexical items are verbs, that is, which elements belong to the corresponding lexical class, is not trivial. The categorization of a lexical element as a verb from a semantic point of view (while passing over grammatical characteristics) is primarily an intuitive decision. It is one that can at best be made on the basis of functional considerations, in describing verbs as elements which typically function as linguistic signs for eventides. They are therefore the surface elements realizing particular ontological entities that represent phenomena that run within time: By the operation of very general cognitive processes that can be termed conceptual partitioning and the ascription of entity hood, the human mind in perception or conception can extend a boundary around a portion of what would otherwise be a continuum, whether of space, time, or other qualitative domain, and ascribe to the excerpted contents within the boundary the property of being a single unit entity. Among various alternatives, one category of such an entity is perceived or conceptualized as an event [in our terms, eventity]. This is a type of entity that includes within its boundary a continuous correlation between at least some portion of its identifying qualitative domain and some portion of the so-conceived temporal continuum - that is, of the progression of time. Such a correlation may rest on a primitive phenomenological experience that can be characterized as dynamism - a fundamental property or principle of activeness in the world. This experience is probably both foundational and universal in human cognition. (Talmy 2000b: 215)

This investigation will focus on exactly those entities that are conceptualized as eventities. In particular, Talmy nicely draws attention to the idea that both a static (what he calls "qualitative domain") and a dynamic aspect (his "progression in time") are correlated in this type of entity, a fact that will play an important role in the following (in particular, cf. Sections 5.4.1. and 7.2.).4 The existence of dynamism in the conceptualization of eventities (which comprise the so-called events, a term often found in the literature, cf. Avrahami and Kareev 1994; Davidson 1980; Higginbotham, Pianesi, and Varzi 2000; Parsons 1990; and Tenny and Pustejovsky 2000b, amongst oth-

12

Survey of research positions

ers) contrasts them with those entities that are conceptualized as more or less time-stable. It is important to emphasize that we do not focus on compositional semantics. Though it is inevitable to include obligatory argument slots (that is, participants of the eventity) into our study in order to supply an appropriate representation of verbal semantics, we nevertheless refrain from presenting compositional approaches. That is, questions of adverbial modification, quantification etc. are not studied in their own right, but only if phenomena emerging from their application reflect characteristics of the eventides in question.5 Hence, all linguistic approaches based on the compositionality principle (e.g., Montague Semantics and formal semantics in general, cf. Link 1979; Cann 1994) are not taken into account. Also, reflexes of the grammatical systems of single languages are disregarded, as for example the explicit linking of semantic roles to syntactic ones, i.e., the question in what way a participant of an eventity is encoded in a particular language (for an overview of contemporary research positions, cf., e.g., Chapter 4 in Wanner 1999). What is relevant for our investigation is merely the fact that languages have particular entries in the verbal lexicon the semantics (or conceptualizations) of which are to be represented as comprehensively as possible by the UER.6 Basically, the UER aims at representing two aspects of lexical semantics: (i) the internal structure of the meanings of verbal lexical items and (ii) the structural relations that exist between verbal lexical items. Our focus rests with the first aspect, as our primary aim is to specify a framework for the representation of verbal semantics. Yet, the second aspect comes into play, as it is hopefully possible in future work to progress in disclosing structural relations with comparisons of representational structures resulting from the first. After an outline of general approaches to lexical semantics in Section 2.1.1., we will have a look at approaches discussing the internal structure of eventities in Section 2.1.2., and of structural relations in Section 2.1.3.

2.1.1.

Approaches to lexical semantics

Several approaches have been developed to capture the meaning of lexical items. Some of them will be introduced briefly in this section, and conclusions for the design of the UER will be drawn.

Lexical semantics of verbs

13

Feature notation for example, as applied by Di Meola (1994) within the framework of cognitive linguistics or applied and criticized in Krohn (1975), aims at characterizing the overall meaning of a lexical item with the help of a set of (in most cases binary) semantic features. Woman, for instance, would be specified with the features [+HUMAN], [+ADULT], and [-MALE] (Lobner2002:133). It is assumed that it is possible to describe all lexical entries of a particular language with a limited inventory of universal semantic features. Especially for bringing out semantic differences between lexical items, the use of features seems to be sensible (the difference between look and see could be captured by describing the former as [+ VOLITIONAL], but characterizing the latter as [-VOLITIONAL]). What is problematic - besides the often assumed binarism - is the fact that the methods for identifying these features cannot be objectified. Moreover, the representation of the meaning of a lexical item as an unstructured set of semantic features seems to be inappropriate (for a criticism, cf. also Lyons 1977a: 322-325). This applies in particular to most verbal lexical items, and expecially to transitive verbs. Their semantics often include relationships between participants that have to be captured. The feature notation of German Mutter 'mother', for instance, would comprise characteristics like [+KIN], [-SAME GENERATION], and [+OLDER], indicating that there has to be an implicit referent to which the features are related, that is, a relationship has to be established which is not present in the model. The UER uses a feature-based mechanism as well: ENUMERATIONS (cf. Section 4.1.5.). These reflect categories whose values can be deployed to list characteristics of other modeling elements. In contrast to semantic features, ENUMERATION types are not necessarily binary. If a characteristic applies, the corresponding ENUMERATION value is listed. ENUMERATIONS are not considered to be objectified, but we hope that in the course of further work done with the UER the carving out of a set of basic cognitive categories that are represented by ENUMERATIONS will be possible. This will be extensively discussed in Section 6.2. Another difference to the feature notation is that in the UER ENUMERATIONS are an extension mechanism mat can be applied to modeling elements. In particular, the UER provides other modeling elements that express relationships between participants (cf. Sections 4.2.2. and 5.1.). These modeling elements may hold or have ENUMERATION values attached to them. In the UER, it is thus neither the values nor the ENUMERATION types themselves that model the relationships, and we are not dealing with unstructured characterizations.

14

Survey of research positions

A philosophical approach towards meaning is the one proposed by Putnam (1979).7 The meaning of lexical items for natural kinds (rather than for eventities or abstract entities) is represented in a vector of four components. Two of these components are relevant to our investigation, namely the one which describes so-called semantic markers and the one which contains the stereotype. Semantic markers are characteristics with a high degree of centrality and they cannot be altered.8 They are central intrinsic features which are ascribed to an entity denoted by the lexical item. The central intrinsic features for German Wasser 'water', for example, would comprise its specification as a liquid. In contrast to semantic markers, the stereotype is the totality of all characteristics associated with the lexical item by speakers and it is tightly linked to the lexical item. For Wasser, the stereotype includes colorless, transparent, and thirst-quenching. The stereotype consists of assumptions about the denoted entity which the language community expects its speakers to adhere to once they have acquired the meaning of the lexical item. Hence, the stereotype can be understood as the minimal standard of shared associations. Obviously, a first structuring of the semantic features is achieved in dividing them into two sets, although the resulting representation may still not be structured enough. Moreover, the problem of how to identify the features remains. The notion of stereotypes has solely been developed for natural kinds, it is therefore not to be applied to the representation of eventities. If it were, it would run into the same problems as the feature notation, for example in not being able to represent relationships between participants of the eventity in question. The identification problem is a problem that the UER has to cope with as well, cf. Section 6.2. What is interesting in Putnam's division into semantic marker and stereotype is that there seems to be a conceptual distinction between primary categorizing features which cannot be altered and which have a high degree of centrality, and other features associated with an item. The UER reflects a similar division in the representation of eventity participants (which clearly comprise natural kinds). We distinguish between ontological categories and other characteristics of participants, as represented by PARTICIPANT TYPES and ATTRIBUTES (cf. Sections 5.4.2. and 4.2.2.). It should be emphasized here that Putnam's notion of stereotype and the UER's notion of STEREOTYPE are unconnected and only happen to be dubbed identically. Since the UER adopts the notion of the UML STEREOTYPE, the name has been kept in order to maintain as much correspondence between the UML and the UER.

Lexical semantics of verbs

15

An approach which tries to avoid the need for identifying necessary and sufficient semantic features is the prototype theory initialized by Rosch's model for human categorization developed in cognitive psychology.9 The notion of prototype is similar to that of a stereotype in that both can be considered as being the result of a perceptual classification by human categorization. It is argued in cognitive psychology that one assigns an entity to a conceptual category not by merely verifying a "simple set of criterial features" (Rosch 1975:193), but by comparing that entity to the prototype of the category. In this way, the fuzzy boundaries of categories can be dealt with. "The prototype is seen as the best exemplar, which is generally associated with the category concerned" (Zitzen 1999:60). For example, robins are the most representative entities for the category of birds in the Anglo-American world.10 Transferring this to lexical semantics is not a simple task.'' The difficulty is grounded in the need of lexical semantics to distinguish a sense level from the referential level to which Rosch's theory applies (for a more detailed discussion, cf. Geeraerts 2002). The meaning of a lexical item which denotes 'best exemplars' of a conceptual category is in particular not the prototypical meaning of a lexical item for that category. For instance, a robin is a prototypical bird, but the meaning of robin is not the prototypical meaning of bird. Thus, a prototype in linguistic terms (as a representation of the meaning of a lexical item) has to be captured differently: it can be regarded as a cognitive picture that is generally associated with a lexical item and serves as a reference point for categorization.12 It is still debated about whether the prototype is a mental picture of a typical (i.e., prototypical) instance of the category or whether it can be an abstract concept consisting of a conjunction of the category's typical features.13 In the latter case, the prototype itself- if it were described explicitly - would have to be characterized via semantic features with all the related problems again. Therefore, either there is no elaborated representation of the prototype and thus of the semantics of a lexical item (but only an intuitive mental picture speakers have, without information on how this picture is to be displayed), or we have to deal with well-known problems again. Thus, in order to be able to obtain precise, suitable representations of the semantics of lexical items, we have to rely on decompositional structuring of the concepts that are to be modeled (in our case eventities). This includes semantic features and other modeling elements that will be categorized and related to each other. The UER framework is designed to meet these require-

16

Survey of research positions

ments in an effective way and to model decompositionally the semantics of verbal lexical items, that is their individual readings.

2.1.2.

Internal structures

This section is devoted to a review of some structural features which are manifest in the semantics of verbal lexical items. We will not discuss structural relations between lexical items (cf. Section 2.1.3.), but conceptual structures evident in the conceptualization of single eventities and thus in the semantics of verbal lexical items. Hence, the issues of this section belong to decompositional approaches to lexical meaning. (For a presentation of some prominent decompositional theories, cf. Section 2.2.) We will begin with a more 'static' aspect of verbal semantics, namely the participants who partake in an eventity and the roles they play within the eventity (Section 2.1.2.1.). Subsequently, we will review aspects of the 'dynamic' structure that are inherent in eventities, thereby arriving at a discussion of Aktionsarten (Section 2.1.2.2.).

2.1.2.1.

Semantic roles and protoroles

Following the online Linguistic Glossary published by the Summer Institute of Linguistics (SIL), a semantic role "is the underlying relationship that a participant has with the main verb in a clause. ... Semantic role is the actual role a participant plays in some real or imagined situation [i.e., in some eventity], apart from the linguistic encoding of those situations" (Loos et al. 1999: WhatIsASemanticRole.htm, accessed on January 31, 2004).14 Although it would be more appropriate to speak of the relationship a participating entity has to the eventity it partakes in (and not with the main verb in a clause), relevant points regarding semantic roles are indicated: their importance for the linking of arguments to syntactic realizations of these arguments, and their invaluableness for describing the semantics of an eventity - apart from the linguistic encoding of the eventity. The latter aspect is the one we focus on in this work, although most approaches to semantic roles are primarily devoted to the former. The number and meaning of the semantic roles are still subject to controversial discussions.15 Historically, the notion of semantic roles (also called deep cases [Case Grammar], thematic roles or theta roles [Generative Gram-

Lexical semantics of verbs

17

mar]) has been initiated by Gruber (1965) and Fillmore (1968), who established two opposing trends in linguistics concerning semantic roles. Gruber proposes a small number of concrete, spatial relationships as semantic roles (which can typically be found with motion verbs). These are roles like source and goal, which are then transferred to more abstract verbal meanings. For example, an experiencer of a psychic state, an intentional agent, and an originating location of a movement are all assigned the source role: So wird zum Beispiel der intentional Handelnde (das Agens) wie in Peter liest, der Träger eines physischen oder psychischen Zustands (der Experiencer) wie in Peter friert und der Ursprung einer Bewegung wie in startet vom Hauptbahnhof unter einer gemeinsamen semantischen Rolle des Ursprungs zusammengefaßt. (Primus 1998:105) [For instance, the intentional actor (the agent) as in Peter is reading, the undergoer of a physical or psychological state (the experiencer) as in Peter is freezing, and the source of a movement as in starts from the main railwaiy station are subsumed under a joint semantic role called source.] This view is referred to as localistic. Jackendoff's approach (1972, 1987), for instance, is based on such a view. Opposed to that, Fillmore works with a larger number of semantic roles, beginning with the following roles in his grammatical framework of Case Grammar: agentive (later on called agent), instrumental, dative (later on recipient and benefactive), factitive, objective (later on patient), and locative (Fillmore 1968:24-25; Primus 1998: 106). Essentially, there are many roles which are non-localistic in nature. In Fillmore's Frame Semantics and the FrameNet project (cf. Fillmore 2004 and Johnson et al. 2001, Section 2.2.3.), even dozens of semantic roles are used, as these are defined separately for each frame. Amongst others, Van Valin and LaPolla (1997) have been following Fillmore in his non-localistic approach. Their approach will be discussed below. For work within the UER, we propose a unified or middle course in Section 6.6., in that roles for prominent participants (such as agent, effector, patient, and theme) are non-localistic, whereas the others are in principle localistic. We suggest a preliminary set of semantic roles that partly follows Frawley's set of semantic roles: Frawley (1992:201-229) lists twelve semantic roles, which he divides into participant roles and non-participant roles. The participant roles comprise the logical actors (agent, author [also called effector], instrument), the logical recipients (patient, experiencer, benefactive), and the spatial roles (theme, source, goal), whereas the non-participant

18

Survey of research positions

roles are not further partitioned (locative, reason, purpose). But as with Larson and Segal (1995:479,481) who mention nine semantic roles, "our list of them is not exhaustive, nor are our definitions final in any sense" (Larson and Segal 1995:486). However, we are aware that most scholars establish their own list of semantic roles. This is still possible when working in the UER framework, because the framework itself does not comprise a fixed set of roles, but merely a mechanism to define roles and to use them in representations of verbal semantics (cf. Sections 5.4.2. and 6.6.). There are some criteria of semantic roles that are accepted by most researchers. One, that we also consider valid, is that each semantic role may appear only once within the domain of a predicate, i.e., in our terms, within a modeled eventity. Another more questionable one is that every semantic role corresponds to one and only one syntactic constituent. (For a description of both principles, cf. Primus (1998:106).) Since the latter criterion, being part of the θ-criterion put up by Chomsky (1981:36), pertains to the linking of semantic roles to syntactic realization of arguments, it does not play a role in the UER in its current stage. An example of a set of semantic roles, together with their explanations as they can typically be found in the literature, is given in Table 1. Table 1. Van Valin and LaPolla's "non-exhaustive" list of semantic roles (1997:8589) Role

Description

agent effector

a willful, purposeful instigator of an action or event; the doer of an action, which may or may not be willful or purposeful; a sentient being that experiences internal states, such as perceivers, cognizers and emoters; a normally inanimate entity manipulated by an agent in carrying out an action; somewhat like an instrument, but it cannot be manipulated; a thing that is in a state or condition, or undergoes a change of state or condition; a thing which is located or is undergoing a change of location (motion); the participant for whose benefit some action is performed;

experiencer instrument force patient theme benefactive

Lexical semantics of verbs Role recipient goal source location path

19

Description someone who gets something (recipients are always animate or some kind of quasi-animate entity); destination, which is similar to recipient, except that it is often inanimate; the point of origin of a state of affairs; a place or a spatial locus of a state of affairs; a route.

The definition of the semantic roles is based on properties which the entities in these roles have to have (although this is not carried out systematically). A more rigorous approach to semantic roles will be adopted here. We will define them via their properties as Van Valin and LaPolla do, but we will also state relations between them (cf. Section 6.6.). We understand semantic roles to be prominent clusters of properties, clusters that can be adapted in single modelings by overwriting or adding particular properties via UER role ATTRIBUTES. This implements the observation of Dowty who abandons the view that semantic roles are discrete categories: The hypothesis put forth here about thematic roles is suggested by the reflection that we may have had a hard time pinning down the traditional role types because role types are simply not discrete categories at all, but rather are cluster concepts, like the prototypes of Rosch and her colleagues. (Dowty 1991:571)

The precise specification of semantic roles, even adjustable to the single eventity that is to be modeled, is one of the UER's levels of rolerepresentation, i.e., of modeling the role a participating entity has within this eventity. Moreover, the prominent participants are explicitly labeled in the UER. They are those participants in the focus of an eventity and whose course of behavior is conceptualized (cf. also Note 218 on p. 374). This second level of role-representation is motivated by the following results of Dowty and of Van Valin and his collaborators. Dowty argues that, since roles types are not discrete categories, entities may have different degrees of membership in a role type. He therefore proposes that only two role types are necessary to describe argument selection efficiently, which he calls proto-agent and proto-patient. The contributing properties for proto-agent and proto-patient are (Dowty 1991:572-573):16

20

Survey of research positions

Proto-Agent 1. volitional involvement in the event or state (as in John picked up the stone) 2. sentience (and/or perception) (as in John fears/sees Mary) 3. causing an event or change of state in another participant (as in John woke up Mary) 4. movement (relative to the position of another participant) (as in The bullet overtook the arrow) 5. existence independently of the event named by the verb (as in John needs a new car)

Proto-Patient 1. undergoes change of state (as in John picked up the stone) 2. incremental theme17 (as in John filled the glass with water) 3. causally affected by another participant (as in John woke up Mary) 4. stationary relative to movement of another participant (as in The bullet overtook the arrow) 5. no existence independently of the event, or no existence at all (as in John built a house)

Though the notions of proto-agent and proto-patient are essentially targeted at the syntax-semantics interface, they are nevertheless important for verbal semantics or eventity conceptualization.18 The participant with the highest number of proto-agent properties is the proto-agent, whereas the participant with the highest number of proto-patient properties attains the role of the proto-patient. The proto-agent is the most active participant, whereas the proto-patient is the participant affected the most. The assignment of both proto-agent and proto-patient properties to participants is not only unproblematic, but even favored, since the aim is to evaluate the roles of the participants in the eventity in comparison to each other and not in terms of absolute values (as is done in the first level of role-representation discussed above). The fact that only two role types are necessary in Dowty's view to efficiently describe argument selection hints at the prominence of at most two participants within eventity conceptualization.19

Lexical semantics of verbs

21

Notions similar to proto-agent and proto-patient are the macroroles actor and undergoer. They have been established within the Role and Reference Grammar framework (cf. Foley and Van Valin 1984; Van Valin 1999b; Van Valin and LaPolla 1997:141-147) and describe generalized semantic roles: They are called 'macroroles' because each of them subsumes a number of specific argument-types (thematic relations). The generalized AGENT-type role will be termed actor and the generalized PATlENT-type role will be called undergoer. (Van Valin and LaPolla 1997:141) Following Van Valin (1993:44), the range of roles that can fulfill the actor role includes agent, effector, experiencer and locative; whereas experiencer, locative, theme, and patient can fulfill the undergoer role. These specific semantic roles occupy points along a continuum of semantic roles of more agent-like or more patient-like roles, the endpoints or anchor points of which are "agent (the willful, volitional, instigating participant) at one end and patient (the non-willful, non-instigating, maximally affected participant) at the other" (Van Valin 1993:41). Conflicts in the macroroles' assignment are avoided by the actor-undergoer scale and the principle stating that the two participants with maximal distance on this scale are assigned actor and undergoer. The locative role as understood here subsumes source, path, goal and recipient; and since the locative is placed somewhere in the middle of the continuum, it is rather unlikely that it is attributed a macrorole and thus the label 'prominent participant'. In contrast to Dowty's approach, these prototypically spatial roles are included in the considerations. In Van Valin and LaPolla (1997:146), the actor-undergoer hierarchy and thus the assignment of macroroles is based on elements of logical structures that represent different verb classes (cf. also Van Valin 1999a). Nevertheless, macroroles are a generalization of underlying 'typical' semantic roles and - in contrast to Dowty's protoroles - do not rely on properties attributed to actor and undergoer. Thus, Schweitzer (2000:13) rightly calls them 'heuristically defined'. Again, no more than two participants are understood as being prominent, because two macroroles can be assigned to an eventity at the most. This is similar to Dowty's approach, cf. the following comparison: What they have in common is the special relevance of only (or mainly) two roles or relations and that these relations are not defined absolutely, but rather as resulting from the relations to the predicate and its other argument(s) when present. (Premper 2001:484)

22

Survey of research positions

In the UER, (currently at most two) participants are marked as prominent participants in modelings of verbal semantics or eventity conceptualization as well. In general, these correspond to the macro- or protoroles described above. Following Role and Reference Grammar, they are dubbed actor and undergoer, and they are labeled by the STEREOTYPES «do» and «undergo», as indicated in Section 5.4.3.

2.1.2.2.

Aktionsart and verb classification

Aktionsart, a term coined by Brugmann in 1885 (cf. Porter 1989:29), is a notion deployed to classify verbs into different categories or classes according to particular properties of the temporal structure of eventities or according to the logical structure of verbs (Dowty 1979:51-52). The categorization is based on inherent properties of eventities. One criterion is dubbed felicity - an eventity is telic, if its temporal structure comprises an inherent boundary, i.e., includes a beginning or end, otherwise we are dealing with an unbounded process (German einschlafen 'fall asleep' vs. German schlafen 'sleep')· Another criterion is termed dynamicity, indicating whether the eventity can be characterized as being an action or a state (German schlagen 'hit, beat' vs. German wissen 'know') (Rapp 1997:16). These two criteria account for the basic distinctions that are made. Other criteria mentioned in the literature are, for example, causativity (German töten 'kill') (Wanner 1999), repetitivity and frequency (German flackern 'flicker') (Bußmann 1990), or interval-basedness and punctiformity (Egg 1994 in his revised classification of Aktionsarten), among others. The design of the UER's dynamic structuring reflects some of these criteria. With regard to the dynamicity criterion, for instance, the UER-STATE embraces two subtypes that reflect this distinction (cf. Sections 4.3.2. and 4.3.3.). Boundedness is indicated in that representations of telic eventities comprise a TRANSITION as part of their dynamic representation (cf. Section 5.2.). Many authors also call Aktionsart aspect,20 although this term is ambiguous. We have to distinguish between the aspectual class of a verb (the Aktionsart or lexical aspect) and its aspectual form (the grammatical aspect, i.e., the particular aspect marker or markers with which it occurs in a given sentence) (Dowty 1979:52). A form of grammatical aspect is, for example, the distinction between perfective and imperfective aspect (he walked vs. he was walking), a phenomenon that is not only present in the distinction be-

Lexical semantics of verbs

23

tween non-progressive and progressive forms in English, but in particular in the verbal lexicon in Slavic languages (Krifka 1989:102). Nevertheless, Aktionsart as a lexico-semantic phenomenon and aspect as a grammatical phenomenon are related to each other. The perfective-imperfective distinction, for example, is considered to have effects on the Aktionsart: be building a house is - in contrast to build a house - not telic (cf. Egg 1994:13). For this reason some scholars claim that Aktionsart cannot be attributed to verb lexemes, but only to complex expressions such as verb phrases (cf., e.g., Zybatow 200la: 31-32). Others such as Rapp see Aktionsart as an inherent property of verbs that can be modified in composition: Demgegen ber betrachte ich Aktionsart als eine inh rente Eigenschaft des Verbs, der eine bestimmte, formal darstellbare Ereignisstruktur (= E-Struktur) entspricht. Diese Ε-Struktur - die also prim r lexikalisch determiniert ist kann durch weitere Satzteile modifiziert werden. (Rapp 1997:17) [Opposed to that, I view Aktionsart as inherent property of the verb to which a particular, formally representable event structure (= Ε-structure) corresponds. This Ε-Structure - which hence is determined primarily by the lexicon - can be modified by additional parts of a sentence.] We will take a third approach in this investigation, one that is essentially detached from linguistic encodings: Aktionsart-like structures will be attributed to eventides. (These can in principle be encoded in lexemes or compositional expressions, but this coding difference, from our eventity-based point of view, is not of primary importance.) Accordingly, a classification will result in an eventity classification and not in a verb classification. For a development of a preliminary eventity classification, cf. Chapter 8. Because of its influence not only in linguistic semantics in general but also in this work in particular, we will introduce the most prominent verb classification in the following, the Aristotle-Ryle-Kenny-Vendler classification (as described in Dowty 1979).21 This classification developed in the philosophical literature as a result of a distinction originally made by Aristotle, who is "generally credited with the observation that the meanings of some verbs necessarily involve an 'end' or 'result' in a way that other verbs do not" (Dowty 1979:52). In the Metaphysics (Book Θ.6, 1048b, 18-35), Aristotle distinguishes between kineseis ('movements') and energiai ('actualities'), a distinction between actions that are goal-directed and those that are not, in that they may in effect reach their goal at any moment. This is close to (but does not correspond to) the distinction between accomplishments and activ-

24

Survey of research positions

ities, or between achievements and states in Vendler's classification, namely the distinction between telic and atelic verbs. In De Anima, Aristotle distinguishes between two senses of energiai, namely one which is equivalent to state and another which is equivalent to activity (Kenny 1963:183). [SJeveral Oxford philosophers of this century [i.e., the 20th century] have had a go at Aristotle's classes, and in ways that are increasingly relevant for linguistic methodology. The first of these was Gilbert Ryle, who in his book The Concept of Mind (Ryle, 1949, p. 149) coined the term achievements for the resultative verbs, to be distinguished from the irresultative activities. (Dowty 1979:53)

Achievements such as win, arrive, cure, build, find are telic verbs, whereas activities such as hear, walk, sleep are atelic. Moreover, Ryle extends this system in stating about achievements: "Some words of this class signify more or less sudden climaxes or denouements; others signify more or less protracted proceedings" (Ryle 1949:149). Thereby, he anticipates Vendler's distinction between achievements (= with sudden climax) and accomplishments (= with protracted proceedings), although his term achievement comprises both achievement and accomplishment in Vendler's terms. Kenny observes "that if φ is a performance verb (his term for the class that corresponds to Ryle's achievements) Ά is (now) 0ing' implies Ά has not (yet) 0ed.' ... But if φ is an activity verb, then Ά is (now) 0ing' entails Ά has ed.'" (Dowty 1979:54) That is, if I am building a house, I have not yet built a house, while if I am living in Munich, I have already lived in Munich. Besides making more grammatical criteria for English available for this distinction, Kenny establishes also a criterion for a precise distinction between activities and states: activities can occur in progressive in English, states cannot (he is learning how to swim vs. *he is knowing how to swim). Zeno Vendler is the first to separate four distinct categories of verbs (Vendler 1967a). His article Verbs and Times appeared (before being reprinted with minor changes as Vendler 1967b) in The Philosophical Review, 1957, 143-160. He distinguishes four "time schemata" (Vendler 1967b: 98) on the basis of restrictions on time adverbials, tenses, and logical entailment22 in order to classify the verbal lexicon, namely: activity, accomplishment, achievement, and state. His canonical examples for these four types are run (for activity), run a mile, draw a circle (for accomplishment), win a race (for achievement), and love somebody (for state) (cf. also Krifka 1989:98). His classification is mainly based on two criteria,

Lexical semantics of verbs

25

one of which is telicity, which distinguishes between activities/states on the one hand and accomplishments/achievements on the other. Vendler explains the difference between activities and accomplishments in the following way, thereby also hinting at the difference between activities/accomplishments and states/achievements: It appears, then, that running and its kind go on in time in a homogeneous way; any part of the process is of the same nature as the whole. Not so with running a mile or writing a letter; they also go on in time, but they proceed toward a terminus which is logically necessary to their being what they are. Somehow this climax casts its shadow backward, giving a new color to all that went before. (Vendler 1967b: 101-102) Both activity and accomplishment "go on in time", are temporally extended and hence they are processes in Vendler's terms, whereas state and achievement do not "go on in time". Following Rapp, this criterion might be termed temporal extension (Rapp 1997:20-21). It is immediately comprehensible for the distinction between accomplishment and achievement: both describe a telic eventity, but an accomplishment entails a process (with a climax), whereas an achievement is a punctiform change of state. However, in order to distinguish between state and activity, Rapp has to impose a different interpretation of the notion of temporal extension, with both categories being related to points in time. Whereas an activity cannot be identified as such at a point in time t, one can say that a state holds at t. Therefore, a state can, in contrast to an activity, be characterized as not necessarily temporally extended, although it normally holds for an interval of time. Assuming the appropriateness of the discussed notion, the four Vendler classes can then be derived from the two underlying parameters of telicity and temporal extension,23 which leads to Table 2: Table 2. The four Vendler classes - Telic + Telic

— Temporally extended State Achievement

+ Temporally extended Activity Accomplishment

Many linguists use Vendler's quadripartition in their theories. Although these four categories might display an exhaustive classification of verbs (a statement which is nevertheless questioned, cf. Engelberg 2000:37), the criterion of temporal extension is applied in an inconsistent way, as we could see in

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Survey of research positions

the previous passage. Moreover, it is a point of contention whether or not the assumed classes are primitive, i.e., basic concerning conceptualization.24 These issues will be resumed in Sections 2.2.5. and 6.9., where Pustejovsky's and our own account of basic eventity types are discussed, and in particular in Chapter 8., where we will develop an eventity classification based on UER-structures.

2.1.3.

Structural relations

We will turn to structural relations within the lexicon in this section. (For a comprehensive overview of the systematic aspects of word meaning and hence of structural relations within the lexicon, cf. also Cruse 1986.) Structural relations are relations that can be identified as existing between or within lexemes, or, to be more precise, between lexical units.25 Since these relations are currently not in the focus of the development of the UER but are to be built in at a later stage, we will not discuss them in detail. In particular, discussing the research that has been done goes beyond the scope of our investigation (cf., amongst others, Cruse 1986; Lyons 1977a, 1977b; Pustejovsky and Boguraev 1996b; Ravin and Leacock 2000b; and Schneider 1988). However, basic conceptual relations underlying particular sense relations have to be expressable in the UER. Moreover, we expect that the UER will easily be able to account for structural relations in the future. Therefore, structural relations are nevertheless of interest in the context of this investigation. There are primarily three phenomena to be discussed. Two of them concern semantic relations between lexical units with typically but not necessarily different lexical forms (except for synonymy which presupposes different lexical forms). The third exclusively concerns structural relations between lexical units with the same lexical form. They are (i) sense relations (with several subnotions), (ii) lexical fields, and (in) polysemy.26 Langer relates (i) and (ii) in the following way: Die Theorie der Sinnrelationen beschäftigt sich mit der Strukturierung des Lexikons durch Sinnrelationen zwischen Lexemen oder Bedeutungen von Lexemen. Zur Beschreibung von Sinnrelationen wird aufgrund semantischer Kriterien ein bestimmter Teil des Vokabulars herausgegriffen, der dann aufgrund der semantischen Beziehungen der in ihm enthaltenen Lexeme strukturiert wird. Ein solcher Teil des Vokabulars, der Lexeme umfaßt, die sich einer gemeinsamen, unspezifischeren Bedeutungseinheit zuordnen lassen, ist ein semantisches Feld. (Langer 1996:29)

Lexical semantics of verbs

27

[The theory of sense relations deals with the structuring of the lexicon by sense selations that hold between lexemes or meanings of lexemes. For the description of sense relations, a particular part of the vocabulary is selected on the basis of semantic criteria, which is then structured by the semantic relations between the lexemes it encompasses. Such a vocabulary part which comprises lexemes that can be assigned to a common, more unspecific semantic unit is a semantic field.]

2.1.3. L

Sense relations and lexical fields

Given the close relation between sense relations and lexical fields, we will start with an overview of the most prominent sense relations, and then move on to a brief discussion of lexical fields. Synonymy (cf. also Cruse 1986:265-294, 2002c) is a horizontal, symmetrical relation between two lexical units with different lexical forms. According to Cruse, two lexical units "would be absolute synonyms (i.e. would have identical meanings) if and only if their contextual relations ... were identical" (Cruse 1986:268).27 The interchangeability of synonyms would also be valid in negated contexts, and absolute synonymy would, moreover, be transitive. But the conditional form of Cruse's specification of absolute synonymy already hints at an argument that is often found in the literature, namely, "that synonymy per se does not exist, and that every distinction of form in every language is used and interpreted by speakers as a distinction in meaning" (Croft 1990:165; cf. also, e.g., Harras 1996). Referring to Cruse, the Linguistic Glossary of the SIL defines synonymy more broadly as "a relationship between two or more lexical units which have identical core semantic components and which differ only with respect to their supplemental or peripheral components" (Loos et al. 1999: WhatIsASynonymLexicalRelation.htm, accessed on February 3, 2004). Unfortunately, the necessity of the two lexical units to have identical lexical forms is not mentioned. In addition, it is far from easy to decide which "semantic components"28 are considered to be in the core meaning and which are supplemental or peripheral. This problem is similar to the one pointed out for semantic features in Section 2.1.1. There are other horizontal sense relations between lexical units which can be subsumed under the general notion of opposition (cf. also Cruse 1986:9395,197-264, 2002b; Lehrer 2002; Lyons 1977a: 270-290; Roelcke 2002; Zaefferer 1999: 14). These are incompatibility, antonymy, complementarity,

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Survey of research positions

conversity, and reversity. Two or more lexical units are incompatible, if they are mutually exclusive in a particular context. Two incompatible, gradable, directionally opposed, contrary lexical units are called antonyms of each other.29 The essence of a pair of complementaries is that between them they exhaustively divide some conceptual domain into two mutually exclusive compartments, so that what does not fall into one of the compartments must necessarily fall into the other. (Cruse 1986:198-199)

Conversity is a relationship specifying the direction of one lexical unit in relation to the other along some axis, i.e., if is above B, then is below A. Another class of "directional opposites consists of those pairs of verbs which denote motion or change in opposite directions" (Cruse 1986:226), such as the basic senses of rise.fall, ascend'.descend or enter:leave. These pairs are called reversives. Hyponymy (cf. also Brown 2002a; Cruse 1986: 88-92; Lyons 1977a: 291295) is a vertical sense relation between two lexical units where a meaning of one lexical unit is more specific than a meaning of the other.30 If A is a hyponym of B, then a meaning of A is fully consistent with a meaning of and adds specific information or properties. In other words, A is_A (kind of) ß, or B is a hyperonym of A. Correspondingly, the converse relation to hyponymy is called hyperonymy. In contrast to synonymy, hyponymy is transitive and asymmetrical. Note that synonymy, e.g., can only be applied to co-hyponyms: Aj,A2, ...,Art are co-hyponyms of each other with regard to ß, if they are all hyponyms of B and belong to the same level of the structure established by the relation (in most cases they are direct hyponyms of B). 'Multi-generalization' is allowed, where each of the hyperonyms represents a different point of view. For example, mother is a hyponym of woman as well as of parent. The conceptual relation underlying hyponymy is captured in the UER by the GENERALIZATION relationship, cf. Sections 4.2.10. and 6.8. The last sense relation to be introduced is another vertical relation, meronymy, (cf. also Brown 2002b; Cruse 1986: 157-180; Lyons 1977a: 311317; Winston, Chaffin, and Herrmann 1987), which is also called partonomy or part-whole relation.^ A lexical unit A is a meronym of a lexical unit B (i.e., ß is a holonym of A), if the meaning of A characterizes the elements of its extension as parts of elements of the extension of B (Zaefferer 1999:1415).32 Langer describes meronymic relations as central for the meaning of some lexemes, as playing a role in the semantic descriptions of other lex-

Lexical semantics of verbs

29

ernes (although they are not a necesssary meaning component), and as being irrelevant for yet other lexemes: Die Meronymierelation ist zentrale Komponente der Bedeutung einiger Lexeme (z. B. Dach als Teil eines Gebäudes), bei der Bedeutung anderer Lexeme spielt sie zwar eine Rolle in der Beschreibung der Semantik, ist aber nicht notwendigerweise Bedeutungsbestandteil (etwa Blatt als Teil eines Schreibblocks). Für wieder andere Lexembedeutungen spielt sie keine Rolle (z. B. bei Tierbezeichnungen). (Langer 1996:33) [The meronymic relation is the central component of some lexemes' meaning (e.g. roof as part of a building, in some other lexemes' meaning it plays a role in the semantic description, but it is, however, not necessarily a semantic component (as in sheet as part of a writing pad). For yet other lexemes' meanings it does not play any role (e.g. for animal names).]

Meronymic relations are at least as diverse as hyponymy, since there are different subtypes. Accordingly, the notion of part can be considered to change depending on the specificities of the relationships. For example, the relation between a tree and a. forest is different from the relation which holds between a chassis and a car. in the first case we have a member-collection relationship, whereas in the second case we have a component-integral object relationship (Winston, Chaffin, and Herrmann 1987:417). Meronymy is asymmetrical and not a priori transitive, a fact that has been extensively discussed in the literature (for example, cf. Cruse 1979). Winston, Chaffin, and Herrmann (1987) claim to have found an explanation of this in the indicated distinctiveness of the different meronomic relations. The underlying conceptual relation of this last vertical sense relation is represented in the UER by the AGGREGATION concept, which is capable of accounting for the different kinds of meronomic relationships. For more details, cf. Sections 5.1. and 6.7. Sense relations structure the lexicon semantically. One well-known example of an electronic lexical database representing the structure as imposed by sense relations is WordNet (cf. Fellbaum 1990, 1996, 1998, 1998b; Miller et al. 1990). "English nouns, verbs, adjectives and adverbs are organized into synonym sets, each representing one underlying lexical concept. Different relations link the synonym sets" (Miller et al. 1990:235; cf. also http://www.cogsci.princeton.edu/~wn/, accessed on January 28, 2004). These synonym sets are called synsets.33 Besides synonymy, which is considered as the basic relation in WordNet, other sense relations come into play. The central organizing principle for noun synsets in WordNet is inheritance,

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that is, the representation of the hyponymic relation: "a hyponym inherits all the features of the more generic concept and adds at least one feature that distinguishes it from its superordinate and from any other hyponyms of that superordinate" (Miller et al. 1990:242). Meronymic relations are not employed for structuring the database, but can be represented by, e.g., pointers (labeled arcs) from one synset to another (Miller et al. 1990:243). Verbs are arranged primarily by a manner-of relation dubbed troponymy: "Troponymy relates two verbs such that one verb specifies a certain manner of carrying out the action referred to by the other verb" (Fellbaum 1998b:213; cf. also Stein 1999:59). Similar approaches are being developed for languages other than English, as for example for those which are included in the multilingual lexical database EuroWordNet (cf. Vossen 1998, 2001): Dutch, Spanish, Italian, English, French, German, Czech, and Estonian (Vossen 1998:75). In its current state, both inheritance and meronomic relations as accounted for in WordNet can be represented by the UER. Moreover, the UER framework can certainly be extended in order to include the other relations. Yet, since the UER is a formal framework and precisely represents different forms and kinds of relations, it will need additional well-specified constructs to account for the diversity in relationships such as the conceptual counterpart of troponymy. The same applies to the representation of semantic affinity or contrast of lexical items that are members of the same lexical field. Lexical fields (also called word fields or semantic fields) result from the lexical structure imposed by sense relations. A lexical field is a set of lexemes whose senses are related to each other. The basic idea of this paradigmatic approach is that lexemes "applicable to a common conceptual domain are organized within a semantic field by relations of affinity and contrast (e.g., synonymy, hyponymy, incompatibility, antonymy, etc.)" (Kittay and Lehrer 1992:3). In particular, the senses of the lexemes are considered to encompass the common conceptual domain and to be bounded by each other within this domain. Lexical field theory posits that semantic relations at least partly constitute the semantics of a lexeme, since the latter cannot be grasped in isolation, but it has to be evaluated in relation to the semantics of other lexemes. Historically, the concept of lexical field was introduced by Trier (1931). Geckeler (1993) considers the following definition by Coseriu to be to the point: Ein Wortfeld ist in struktureller Hinsicht ein lexikalisches Paradigma, das durch die Aufteilung eines lexikalischen Inhaltskontinuums unter verschiedene in der Sprache als Wörter gegebene Einheiten entsteht, die durch

Lexical semantics of verbs

31

einfache inhaltsunterscheidende Züge in unmittelbarer Opposition zueinanderstehen. (Coseriu 1967:294) [A word field is from a structural point of view a lexical paradigm, which is formed by the partition of a lexical continuum according to different units given in the language as words, which themselves are in direct opposition to each other due to simple meaning distinctions.]

A lexical field can be described by an archilexeme, an abstract element, the meaning of which corresponds to the combination of the semantic features which are common to all elements of the lexical field (without, in fact, naming or identifying these features).34 This archilexeme can, but need not, be lexicalized in the particular language. Some field theorists such as Lutzeier restrict the field to lexemes belonging to the same syntactic class (Lutzeier 1981:139), whereas others, as e.g. Lehrer and Kittay, "see an important part of the lexical study to look at semantically related words belonging to various parts of speech" (Kittay and Lehrer 1992: 3). As with other structuralistic approaches to lexical semantics, lexical field theory faces the problem of delimiting the entities described, in this case the lexical fields themselves (Langer 1996:30). Moreover, it seems that the decision of which lexemes are members of a lexical field rests upon intuitive grounds in this approach. Accordingly, a confirmation of the archilexeme might only be possible after establishing the field itself. Although field theory has been neglected by most linguists during the past years - "es kann ... nicht die Rede davon sein, daß die Wortfeldforschung gestorben sei, daß sie 'megaout' sei, aber als quicklebendig und kraftstrotzend, kurz als 'megain' wird man ihre derzeitige Befindlichkeit auch nicht einschätzen können" (Geckeier 1993: 11) [it cannot... be said that field theory has died, that it is 'mega-out', but one cannot judge it either as being full of life and bursting with vigour, in short, as 'mega-in'] - the interested reader is referred to, for example, Geckeler 1996, 2002; Cloning 2002; Grandy 1992; Kittay 1992; Lutzeier 1993, 1995; Lyons 1977a: 250-269; Schneider 1988:30-39; and, in particular, Lutzeier 1981, 1993.

2.1.3.2.

Polysemy

The study of polysemy, or of the 'multiplicity of meanings' of words, has a long history in the philosophy of language, linguistics, psychology, and literature. The complex relations between meanings and words were first noted

32

Survey of research positions by the Stoics (Robins 1967). They observed that a single concept can be expressed by several different words (synonymy) and that conversely, one word can carry different meanings (polysemy). (Ravin and Leacock 2000a: 1)

Synonymy entails prima facie the existence of a sense which is common to all the lexemes in question, whereas a polysemic lexeme comprises different senses, i.e., there are different readings for one identical lexical form. Relating senses and lexical forms, absolute synonymy is a (7 : n)-relation, whereas polysemy has to be regarded an (n: 7)-relation.35 There are, in principle, two (n: 7)-relations (and thus cases of lexical ambiguity), namely polysemy and homonymy. In contrast to homonymy with lexical units incidentally sharing one lexical form, the identity of the lexical forms of lexical units which are part of the same lexeme is not arbitrary - the lexical units share one lexical form on systematic grounds. Polysemy is not only economic by minimizing the number of lexical forms but also, in a sense, it reflects structural iconicity: the identity in form is understood as a common ground of semantic characteristics. However, this commonness does not necessarily include a common element for all the meanings of a polysemous lexeme. According to Apresjan (1974:15), it suffices if each of the meanings in question is linked with at least one other meaning. Because of this systematicity, we will focus on the structural relation of polysemy in this section and leave homonymy aside. Nevertheless, it should be noted that the difference between homonymy and polysemy is easier to explain in general terms than it is to define in terms of objective and operationally satisfactory criteria (Lyons 1977b: 550). Es ist allerdings nicht immer eindeutig, ob eine Wortform einen oder mehrere Begriffe ausdrückt, und Polysemie kommt in verschiedenen Abstufungen vor. Ganz klar sind Fälle von Homonymie wie Kiefer (der Baum und der Schädelknochen), in denen dieselbe Wortform reiner Zufall ist und keinerlei Bedeutungszusammenhang signalisiert. Wenn, was manchmal der Fall ist, Homonyme eine gemeinsame etymologische Herleitung haben [as, for example, German Bank ('bank' vs. 'bench')], ist diese meistens nicht mehr transparent für den normalen Sprachbenutzer. Dagegen sind in einem Fall wie schlagen (Der Mann schlägt den Hund l Becker schlug Agassi l Mutter schlägt die Sahne) die verschiedenen Bedeutungen sicher weniger zufällig oder obskur und weisen auf eine begriffliche Verwandtschaft hin (man bemerke, daß es in solchen Fällen die gleiche Polysemie auch in anderen Sprachen gibt; vergleiche das englische Verb beat). (Fellbaum 1996:219)36

Lexical semantics of verbs

33

[It is, however, not always clear whether a word form expresses one or more concepts; and polysemy occurs in different degrees. Obvious are cases of homonymy such as Kiefer ['pine', 'jaw'] (the tree and the skull bone), in which the same word form is pure coincidence and does not signal any connection of meanings. If, as sometimes is the case, homonyms have a common etymological derivation [as, for example, German Bank ('bank' vs. 'bench')], this is in most cases not transparent for the normal language user any more. In contrast, the different meanings are certainly less coincidential or obscure in a case like schlagen ['beat'] (The man beats the dog I Becker beat Agassi I Mother is beating [whipping] the cream), and they indicate a conceptual relationship (note that in such cases the same polysemy exists in other languages; compare the English verb beat).]

Although it is certainly not the case that the readings of different languages' polysemous lexemes that are translatable into each other coincide (cf. German die Uhr schlägt acht vs. English the clock strikes eight), it is an interesting question of how overlapping subsets (since overlaps occur) might be characterized. One could speculate that the overlapping polysemic clusters can be expected to represent basic concepts and conceptually self-evident systematic alternations of these senses. There is a particular kind of polysemy that is important, namely regular polysemy (sometimes also referred to as productive or systematic polysemy, cf. Ravin and Leacock 2000a: 9): Polysemy of the word A with the meanings a, and a} is called regular if, in the given language, there exists at least one other word B with the meanings bj and bj, which are semantically distinguished from each other in exactly the same way as a, and aj and if a,· and hi, aj and bj are nonsynonymous. (Apresjan 1974: 16)37

Apresjan suggests that many types of regular polysemy are productive; "in other words, for any word which has a meaning of type 'c,·', it is true that it can be used in a meaning of type 'c/ as well" (Apresjan 1974:18 [with A, B of the original substituted with c/, c, in order to avoid confusion with the previous quotation]). For example, any lexeme comprising the meaning of 'vessel' can designate also 'the quantity of a substance that the vessel is capable of containing'. Moreover, there are many occurrences of polysemy which are not regular in the above sense, but are nevertheless common and can be understood to be the result of a particular operation. One operation of this kind is causativation. Causativation can be found in the verbal domain we

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focus on, and it also plays a role in the eventity classification we propose in Chapter 8. It often operates between intransitive and transitive readings and is thus applicable to describing polyvalence: (1) a. Der Ball rollte unter die Bank. The ball rolled under the bench.' b. Alexander rollte den Ball unter die Bank. 'Alexander rolled the ball under the bench.' (2) a. The window broke. b. John broke the window. (Dowty 1979:43) (3) a. The horse galloped. b. John galloped the horse. (Dowty 1979:43) From this observation the idea of dynamically capturing regular polysemy developed, with the expectation that it would be possible to overcome the critical aspects of, e.g., feature notation (Behrens 1994: 1). For instance, Pustejovsky turned towards creative aspects of the lexicon (cf., e.g., Pustejovsky 1991a, 1995; and, for a review article on Pustejovsky 1995, Behrens 1998). He supports the view that the lexicon is a highly organized, content-rich structure that possesses a remarkable degree of systematicity and generativity. Rather than assuming a fixed set of primitives, he assumes a fixed number of "generative devices" (Pustejovsky 199la: 409) that can be seen as constructing semantic expressions. His qualia structure, being part of a representation mechanism for lexical items, has been developed in order to explain regular polysemy. We will touch on the qualia (as a part of his decompositional approach) in Section 2.2.5., discuss eventities including causativation in Section 8.3., and present an example of polysemy in Chapter 9.

2.2.

Approaches to decompositional semantics

In this section, we will introduce five different approaches to decompositional semantics?* We will mainly deal with decompositional approaches that have been developed in the last two decades, but recommend Dowty 1979 for an overview of previous decompositional approaches. Because of its impact on

Approaches to decompositional semantics

35

semantic research, we will start with one older approach, Generative Semantics, which emerged as a differentiation from Katz and Fodor's (1963) semantics conception. Besides Generative Semantics, approaches proposed by Jackendoff, Fillmore, Wunderlich, and Pustejovsky are discussed and assessed with regard to the UER. One result of the overview in Section 2.1.1. was that, in order to come up with an appropriate representation for a verb's semantics, a decomposition displaying the internal structure of the verb's semantics is necessary. In our cognitive approach, this is tantamount to the display of the conceptual structure, i.e., the eventity structure in question. We understand eventities as entities that are composed of conceptual components (cf. also Bierwisch and Schreuder 1992:23). Therefore, we adopt the decompositional view, which is at variance with its 'holistic' counterpart that has been rigorously advocated by Fodor (e.g., 1975,1983).39 Nevertheless, we will not conceal the criticism that is targeted at decompositional approaches (cf., e.g., Stein 1999:70-71) and that is relevant in our context.40 One of these criticisms is that lexical decomposition results in the attempt to define lexemes, although only a few lexemes can indeed be defined. Moreover, it is claimed that prototypical effects cannot be captured by decomposition. The first allegation is correct as long as lexical decomposition is used with the aim of being exhaustive. Partial or purposeful decomposition is nevertheless desirable, that is, a decompositional approach that characterizes the verb in question by picking out relevant aspects with regard to semantic restrictions and the inner structure of the verb, or with regard to the modeling purpose. Yet, if decomposition is done by applying an artificial explication language, the 'definition problem' naturally stands back, leaving us with remaining reflexes of natural language use in the representation, if any. Thereby, potential problems of the semantic representation (i.e., possible circularity) are much easier to avoid or, if they occur, are overtly enunciated and pinned down in a systematic and concise way. This applies to the UER, which uses not only an artificial explication language with a precisely specified syntax and semantics, but expresses important structural features via graphical and hence non-linguistic modeling elements. Concerning the second allegation (cf. also the treatment of prototype theory in Section 2.1.1.), it has to be stated that the modeling of prototypical effects is in fact easier with decomposition than without. Prototypical instances stand out not only for possessing the necessary and therefore obligatory fea-

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tures for membership in a particular category, but they also stand out for instantiating features that characterize them as being 'at the core' of that category, i.e. as being prototypical. A precise modeling of meaning, as is possible in the UER framework, can therefore help to distinguish what is prototypical about an entity. Finally, recall the positive evidence which militates in favor of decomposition. Following Bierwisch and Schreuder, we consider the decomposition hypothesis to be strongly supported by e.g., speech errors resulting in lexical mis-selection and cases of systematic lexical relations which can be captured in a straightforward way by decomposition (Bienvisch and Schreuder 1992:28).

2.2.1.

Generative Semantics

Generative Semantics has been a highly-influential approach towards representing the meaning of lexical items in a structured way. The meaning of a verbal lexeme is displayed as a structured complex of primitive elements. Generative Semantics being an offset of the abstract syntax as presented in Chomsky (1965), its originators, Lakoff, McCawley, Ross and others, started in the late 1960's to deny the existence of a purely syntactic deep structure. They argued that there was no such "linguistically significant level 'between' semantic representation and surface syntactic representation" (McCawley 1976a: 155).41 Thus, in Generative Semantics, surface structures are not generated out of the deep structure by transformational rules (and interpreted by phonological rules yielding the phonological representation), with the semantic interpretation being the result of an application of semantic rules to the deep structure (Lyons 1977b: 412). Instead, it was suggested that the 'deepest' level of underlying syntactic structure would turn out to have all the properties formerly attributed to semantic representation. This 'level' of linguistic structure was to fully represent the meaning of a sentence, but not to contain words specific to a single natural language (Dowty 1979:43-44). No distinction was made by the Generative Semanticists between the deep structure of a sentence and its semantic interpretation.42 As it was assumed that most 'surface' English words would be represented at this deepest level by complex expressions rather than by single elements (indeed, this view was no doubt taken over without question from the decomposition approach of earlier linguists), attention turned to the question of just

Approaches to decompositional semantics

37

how individual lexical items of a language came to replace multiple parts of an underlying tree in the course of a derivation. (Dowty 1979:44)

The most influential solution to this problem was presented by McCawley. He suggested for the (in the meantime well-known) example verb kill that it should be analyzed into the components CAUSE, BECOME, NOT, and ALIVE. In his representation, which is displayed in Figure 1, the two participants χ and y of the eventity are included as well - "one of whom causes the event in question and the other of whom dies in that event" (McCawley 1976a: 157).

ALIVE

Figure 1. Semantic representation of* killed y (McCawley)

No part of this representation represents a constituent of a sentence or a lexical item. McCawley does not explain the emergence of the representation in Figure 1 explicitly. He only states that kill can be resolved as cause to die and that die is itself semantically complex, meaning 'cease to be alive' or 'become not alive' (McCawley 1976a: 157). The second paraphrase, thus, indicates how the structure developed, although neither the exact tree structure nor the characterization of the nodes as sentences (S) are clarified. In order to arrive at a representation of the lexical item kill, McCawley suggested that transformations rearrange parts of the tree to form a single constituent before the lexical insertion transformation could insert the single word kill (Dowty 1979:44). For this purpose, he proposed the predicate raising transformation, which attaches a predicate (elements such as CAUSE, BECOME, NOT and ALIVE in the tree) to the predicate of the next higher sentence. Thereby, one node vanishes and y is automatically raised. Some of the derivation's stages of the surface structure χ killed y43 from Figure 1 are depicted in Figure 2.

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Survey of research positions

CAUSE

χ

CAUSE

BECOME

NOT

CAUSE

ALIVE

BECOME

BECOME

NOT

NOT

ALIVE

ALIVE

Figure 2. Stages of deriving the surface structure for χ killed y (McCawley) At the last stage, the predicates form a single constituent, and the lexical insertion transformation replaces the sub-tree consisting of exactly these elements with kill (Dowty 1979:45). Nevertheless, according to McCawley, the predicate raising transformation is optional, since there is no need to perform all stages of the derivation (McCawley 1976a: 158). For example, if the last step was not performed, one could obtain sentences such as John caused Harry to die. Moreover, the order of predicate raising steps is not fixed: if NOT was raised in the first step (instead of ALIVE), one would obtain χ caused that y ceased to be alive after lexical insertion. In other words, several ways of clustering the predicates and thus several configurations are possible. Generally, predicate raising allows for configurations which correspond to lexical gaps. Leaving the predicate raising transformation unrestricted in such a way, McCawley imposes the following "universal surface structure constraint" in order to exclude the generation of lexical gaps: "a surface structure is well-formed only if all its terminal nodes bear lexical items" (McCawley 1976a: 159). Furthermore, only predicates or predicate clusters being 'neighbors' in the tree (i.e. a predicate or predicate cluster and the one of the next higher or lower sentence S) can be fused. For example, the predicate BECOME is fused with the predicate cluster NOT-ALIVE in Figure 2. In the supplemented endnotes of his (1976) reprint of the 1968 article, McCawley comments on English cause being used in a variety of ways, whereas

Approaches to decompositional semantics

39

the predicate CAUSE of his proposal is restricted "to a relationship between a person and an event" (McCawley 1976a: 164). In the original paper, he "bandied about cause and CAUSE with gay abandon and accordingly was grossly inconsistent" (McCawley 1976a: 164) in, for example, using CAUSE to represent paraphrases in the order of '* does (something) which causes ...' (McCawley 1976a: 165). Correcting this, McCawley notes that a better representation of killed y would display the causation as a relationship "between an action or event and an event" (McCawley 1976a: 164), including a representation of the first "action" or "event" by the (new) predicate DO. Of course, McCawley was only interested here in illustrating the method of lexical insertion, and perhaps did not intend this to be taken too seriously as an analysis of kill. Nevertheless, the analysis became a standard one, and there are fairly clear reasons why it would seem motivated... (Dowty 1979:45-46)

This might be the reason why much of the information about a verb's semantics is not included in McCawley's decomposition structure (as for example semantic roles or characterizations of the participants). Moreover, the notation is unsatisfactory from a semantic point of view, because the semantics that is represented in underlying trees like these seems to be taken at random. Yet there are some significant, although unfortunately just implicit ideas: Besides the CAUSE predicate, which in McCawley's later conception is a relationship between two eventities, the predicates DO and BECOME are interesting. DO represents actions or, more generally, eventities causing other eventities (only eventities being a cause are marked by DO). BECOME can be considered a predicate indicating transitions. Predicates like DO ("Tätigkeitsprädikat" [action predicate]), BECOME ("Zustandsveränderungsprädikat" [change of state predicate]) and CAUSE ("Verursachungsprädikat" [causation predicate]) are, among others, modified and with more fine-grained specifications, still used in semantic representations, cf. Rapp (1997:31-33).44 In her approach, as in most of the contemporary ones, DO does not describe causing eventities, but actions which are performed by the actor, i.e., DO serves as an activity marker (cf. also Van Valin and LaPolla 1997: 103).45 The status of the predicates NOT and ALIVE of McCawley's representation cannot be interpreted as easily. To consider NOT a predicate over predicates is very questionable, as Bartsch and Vennemann (1972:15) have correctly pointed out with regard to Lakoff's work. The fact that ALIVE represents a state is only overt in the paraphrases McCawley uses, as in 'cease to be alive'. Unlike contemporary approaches (such as Jackendoff's, cf. Sec-

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Survey of research positions

tion 2.2.2.), McCawley does not establish a statal BE predicate ("Zustandsprädikat" [state predicate] in Rapp's terms). Hence, predicates in Generative Semantics cannot exclusively be classified as denoting sortal properties or basic eventity types present in the decomposition, but are sometimes mingled with the content of sortal descriptions. As a result, the sortal descriptions are then themselves not explicated in the structure. For instance, BECOME represents transitions and is accordingly a marker for a sortal property or basic eventity. In contrast to that, there is no representational element for state - any statal characterization is left implicit, such as in the predicate ALIVE. The UER will overcome this shortcoming by representing basic eventity types (cf. Section 6.9.) as graphical constructs in the dynamic core (cf. Section 5.4.1.) and giving their content as expressions contained in or attached to these graphical constructs. In the context of discussing Generative Semantics, general weaknesses of decompositional approaches have been revealed as well. Immler, for example, mentions the 'definition problem' of decomposition, which has been touched on in Section 2.2.46 Other points of criticism not directed to the decompositional nature of Generative Semantics concern the assumption of movement transformations: "The retention of Chomsky's concept of a movement transformation leads to another unwarranted assumption of 'generative semantics', the assumption that underlying representations of sentences, i.e. 'logical forms', are linearly ordered" (Bartsch and Vennemann 1972: 17). In order to be able to represent verbal semantics in a fine-grained way and to allow for the representation of slight meaning differences between verbs, the UER dismisses linear representations and uses a two-dimensional space instead. Moreover, a graphical representation as implemented in the UER does not only make sense because it often provides an intuitive overview and enables the grasping of modeled content more easily. It is also sensible because the graphical constructs are meaningful within the model, i.e., particular graphical constructs convey particular sortal meanings.

2.2.2. Jackendoff's Conceptual Semantics An approach that abandons linearity is Jackendoff's Conceptual Semantics. The starting point of Jackendoff's analysis was that syntactic phrases were considered to correspond to certain structured conceptual entities (Wunderlich 1996b: 170).

Approaches to decompositional semantics

41

The basic hypothesis underlying Conceptual Semantics ... is that there is a form of mental representation called conceptual structure that is common to all natural languages and that serves as the 'syntax of thought'. (Jackendoffl991:10)

Within this framework, a lexical item can be seen as a correspondence between well-formed fragments of phonological structure, syntactic structure, and conceptual structure (called lexical conceptual structure [LCS]): The leading questions of lexical semantics then come to be framed as: (a) What fragments of conceptual structure can be encoded in lexical items (of, say, English)? (b) When lexical items are combined syntactically, how are they correspondingly combined in conceptual structure, and what principles license these correspondences? (Jackendoff 1991:11)

The latter question indicates that Conceptual Semantics is concerned with representing conceptual structures that correspond to phrases and therefore, the primary focus does not lie on verbal semantics. But as verbs, if present, are considered to be the heads of the phrases they occur in, much of the theory of Conceptual Semantics has been dealing with verbal semantics and argument structure. To gain an impression of the notation employed in Conceptual Semantics, consider the syntactic structure in (4a) and the corresponding conceptual structure in (4b) (Jackendoff 1991: 13): (4) a. [s Dv/> Bill][Vp[v went][/>/>[/> mlo][NP the house]]]]

b. [Eveat GO ([Thing BILL], [Path TO ([/>/«« IN ((Thing HOUSE])])])] Paralleling the notation for syntactic structure, the square brackets in (4b) identify conceptual constituents: Each constituent is labeled as belonging to a major conceptual category or 'semantic part of speech' - one of the kinds of entities the world is conceptualized as containing, for example Thing (or physical object), Event, State, Path (or trajectory), Place (or location), Property, Time, and Amount. (Jackendoff 1991:13)47

Besides establishing ontological categories this way (and thereby typing entities), the expressions in small capitals are considered to denote 'conceptual content'. In (4b), IN, TO, and GO are of particular interest. These are place-,

42

Survey of research positions

path-, and event-functions mapping certain conceptual categories into certain conceptual categories. Both conceptual categories and functions are considered primitives in early Conceptual Semantics (cf. Jackendoff 1983). For example, "TO is a one-place function that maps a Thing or Place into a Path that terminates at that Thing or Place" (Jackendoff 1991:13).48 The formation rules of the most important functions for the spatial domain are given in (5) (cf. Jackendoff 1990:43^44).49 (Curly brackets indicate alternatives. ORIENT is used "for specifying the orientation of objects (The sign points toward New York)", EXT "for the spatial extension of linear objects along a path (The road goes from New York to San Francisco)" (Jackendoff 1990:44).)

(5) a. [PLACE] -* [P[ace PLACE-FUNCTION ([THING])] TO

FROM

b. [PATH]

^ / Γ Γ THING Ί Ί λ

TOWARD AWAY- FROM Path

c. [EVENT]

VIA PLACE

]\)

VIA

[Event GO ([THING], [PATH])] [Event STAY ([THING], [PLACE])]

[State BE ([THING], [PLACE])] d. [STATE]

[state ORIENT ([THING], [PATH])]

EXT ([THING], [PATH])] e. [EVENT]

CAUSE Event

THING EVENT

In (1972), Jackendoff worked with another function (without having established the conceptual categories at that time): "CHANGE takes three arguments, an individual, an initial state, and a final state; presumably it will ... be semantically primitive" (Jackendoff 1972:39). This CHANGE-function can be understood as describing general transitions. This is supported by the fact that Jackendoff allows for other semantic information to be added in order to further restrict the nature of the change as locational or possessional, for example. However, within his motional model he later abandons the CHANGEfunction in favor of the GO-function.50 Thereby, he follows Gruber's localistic approach: "all predicates are analysed by means of the semantic functions

Approaches to decompositional semantics

43

based on motion verbs" (Ravin 1990:78). The restriction to a motional model is based on a psychological claim, namely, that in exploring the organization of concepts which lack perceptual counterparts, we do not have to start all over again. The mind is said to adapt "machinery that is already available, both in the development of the individual organism and in the evolutionary development of the species" (Jackendoff 1983:189). Hence, it is expected to use spatial organization for further organizational purposes:51 Thematic Relations Hypothesis (TRH) In any semantic field of [EVENTS] and [STATES] the principal event-, state-, path-, and place-functions are a subset of those used for the analysis of spatial location and motion. Fields differ in only three possible ways: a. what sorts of entities may appear as theme; b. what sorts of entities may appear as reference objects; c. what kind of relation assumes the role played by location in the field of spatial expressions. (Jackendoff 1983:188) The semantic parallelism between the motional and other fields is formally expressed by using subscripted spatial functions as in (6), an example from the temporal field (Jackendoff 1983:190). (6) The meeting is at 6:00. [State BETemp([Event MEETING], [piace XTTemp([Time 6:00])])]

Although Jackendoff is probably right in assuming that basic human experience forms the starting point for conceptual organization, it is questionable whether spatial organization is the only fundamental ground extensions emanate from. But even if it were so, it has to be wondered whether conceptualization is always falling back onto spatial and motional organization, or whether by contrast abstraction from the experienced field enables extensions. We support the latter assumption and thus plead for a kind of representation Jackendoff started off with, a representation with basic eventity types similar to the transitional function CHANGE. That is, we propose to work with basic eventity types that are abstracted away from particular conceptual domains - such as the concept of transition is, which is implemented by the UER TRANSITION (cf. Section 5.2.). Those types' variants are covered by characterizing the participants and their roles and states. Jackendoff is probably the most prominent supporter of the predicate dependent approach, an approach in which thematic relations of verbs are described by their position in sublexical predicates or in functions which represent the 'conceptual content' of these verbs.52

44

Survey of research positions In other words, thematic relations are to be reduced to structural configurations in conceptual structure; the names for them are just convenient mnemonics for particularly prominent configurations. (Jackendoff 1987: 378)

An argument in favor of viewing semantic roles as mnemonics for particularly prominent property clusters is certainly the fact that there are many facets of semantic roles and that the role names introduced in Section 2.1.2.1. do not suffice to describe the variety of characteristics of eventity participants. In this regard we follow his statement that terms such as theme and agent are not primitives of semantic theory (Jackendoff 1987:378-379) (but, in our view, collections of relational properties). For Jackendoff, semantic roles are names for structural positions. They "are relational notions defined structurally over conceptual structure, with a status precisely comparable to that of the notions Subject and Object in many syntactic theories" (Jackendoff 1987:379).53 Unfortunately, this purely structural approach cannot explicitly account for any similarities (or even the identity in particular cases) or relations between semantic roles, as the feature-based approach advocated in the UER can. Up to this point, Jackendoff's representation is still linear. In (1987), he notices that "the S&C [Semantics and Cognition] theory of conceptual structure is if anything not rich enough" and carries on: "The enrichments to be proposed will be highly speculative and incomplete, but I think they are indicative of the directions in which research should proceed" (Jackendoff 1987:394). A revised version of these (1987) enrichments can be found in Jackendoff (1990). The impulse for the first enrichment and thus the abandonment of linearity is the desideratum of a linking theory. For this purpose, in addition to the thematic tier (what has been the conceptual structure), Jackendoff introduces a second tier, the action tier, as part of the conceptual structure. The thematic tier deals with motion and location, whereas the action tier deals with agent-patient relations (in (1990), Jackendoff speaks about actors instead of agents). AFF ('affect', which substituted the former more restricted ACT function)54 is the basic function of the action tier, whose interpretation is that the first argument (the actor) affects the second argument (the patient). Consider (7), for example:55 (7) a. The car hit the tree. Theme Goal Actor Patient

thematic tier action tier

Approaches to decompositional semantics

'

Event

INCH ([BE ([CAR], [AT ([TREE])])]) AFF ([CAR], [TREE])

45

thematic tier action tier

Another (1987) enrichment is the introduction of a third tier, the temporal tier.56 "Different kinds of events, with different aspectual properties, will be associated with different structures in the temporal tier" (Jackendoff 1987: 398). Two primitives are suggested: P, a point in time, and R, a region in time. A "point-event", such as Bill sneezed, is associated with P; processes, such as Bill ran around, are associated with a region R. An achievement, such as Bill arrived, is associated with a region R bounded at the end by a point P that highlights the time of arrival: its temporal tier is R P (Jackendoff 1987: 398). The well-formedness constraint on this tier is that Ps and Rs must alternate. The temporal tier serves to link the thematic and action tiers (Ravin 1990: 89). An example of the conceptual structure including all three tiers is given in (8) (Jackendoff 1987: 399; his abbreviated representation is adopted here). The association lines are to be understood as connecting a P or R to an entire event. (8) Bill threw the ball into center field.

[CAUSE (BILL, 00 (BALL,

FIELD

>»

[ACT (BILL, BALL)] Unfortunately, this representation is neither wholly self-explanatory nor explained by Jackendoff. He aims at showing that, using the temporal tier, it is possible to classify the acting of Bill on the ball temporally, namely to show that Bill only initiates the motion of the ball. This is depicted by connecting the initial point P to the action tier. What is not overt though is to which subevent the temporal tier belongs (to the CAUSE- or GO-event?)57 and why two path-functions are encoded within the path-argument of GO. Of course, it is possible for the human interpreter to understand that this is done in order to encode both source and goal - but within Jackendoff's Conceptual Semantics framework it is not permitted to have two path-functions as second argument

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Survey of research positions

of the GO-function (cf. also Note 50 on p. 357). Nevertheless, the temporal tier is interesting insofar as it includes the distinction between durative (R) and non-durative (P) parts of eventities, although in Example (8) it does not become clear which parts of the eventity the R and the second P represent. Durativity as an important feature is also reflected in the design of the UER, in that the basic modeling elements of dynamic structuring, STATE, TRANSITION, and SIGNAL, can be marked as durative (cf. Sections 4.3.3., 4.3.8., and 5.2.1.). Two more extensions will be touched on, starting with the insertion of selectional restrictions to limit the range of entities permissible as functional arguments. In other words, "selectional restrictions are essentially explicit information that the verb supplies about its arguments" (Jackendoff 1987:385). In order to deal with semantic restrictions on arguments that go into more detail than the conceptual structure (Jackendoff 1987:384), Jackendoff introduces "semantic markers". Semantic markers seem to be comparable to Putnam's semantic markers as discussed in Section 2.1. and the ontological categories as expressed by the UER's PARTICIPANT TYPES (cf. Section 5.4.2.). They are integrated into the lexical conceptual structure by appearing within the corresponding constituent. For example, the thematic tier of the lexical entry for drink is supposed to be (9),58 where the object (which is indexed by j) is restricted to being a LIQUID (Jackendoff 1987:386). (9) [Event CAUSE ([Thing ],·, (Event GO ([Thing LIQUID];, [Path TO (\piace IN ((Thing MOUTH OF ([Thing ]/)])])])])]

The information of the semantic marker has to be merged with a NPconstituent which appears as the direct object: In Harry drank the wine, Argument Fusion combines the reading of wine with the constituent [Thing LIQUID];; the redundant marker LIQUID is deleted. In Harry drank it, the result of merger is the reading 'contextually specified liquid', the former part coming from the pronoun and the latter from the verb. In Harry drank, there is no NP to be merged with thej-indexed constituent, so the reading is merely 'liquid' and otherwise unspecified. In Harry drank powder, fusion cannot apply because powder, with the marker SOLID, clashes with LIQUID. (Jackendoff 1987:386) In Jackendoff's approach selectional restrictions on arguments are of the same form as representations of implicit arguments (such as [Thing BUTTER]

Approaches to decompositional semantics

47

in butter), apart from the fact that arguments with selectional restrictions are indexed (such as j in [Thing LIQUID]^ in the quotation), in contrast to implicit arguments. The last extension to be mentioned is Jackendoff's move towards a more abstract, feature-based metalanguage. Whereas in Jackendoff (1983, 1987, 1990), functions (such as CAUSE and GO) and conceptual categories (such as Thing, Place) are viewed as primitives (even though in Jackendoff (1990:108) all functions in one thematic tier can be supplemented by features like, for example, [± CONTACT]),59 Jackendoff starts to decompose these 'primitives' further in (1991).60 For instance, the category Thing as used above is intended to denote individuals only. Jackendoff (1991) argues, however, that individuals need to be brought under a larger supercategory which also takes in groups, substances, and aggregates. He proposes to call the supercategory Material Entity (Mat for short), and to recognise two binary features ±b (bounded) and ±i (internal structure) so as to decompose the notions of individual, group, substance and aggregate as follows: Mat, +b, —i: individuals (e.g. a pig, someone) Mat, +b, +i: groups (e.g. a committee) Mat, —b, —i: substances (e.g. water) Mat, —b, +i: aggregates (e.g. pigs, people) (Goddardl998:65) Place and Path on the one hand and State and Event on the other are seen as instances of the supercategories Space and Situation respectively, which in each case are distinguished by a feature for directionality (DIR). Other functions are introduced, among them a pair that relates boundaries to what they are bound (BD [Bounded] and BDBY [Bounded by]) (cf. also Goddard 1998:66). This enables Jackendoff to decompose the former primitive TO-function as follows in (10) (Jackendoff 1991:36):

(10) TO X =

DIMldDIR . Space

BDBY

([τ hing/Space X]) .

"That is, TO specifies a 1-dimensional bounded directed Space (i.e., a bounded Path), bounded on its positive end by the Goal" (Jackendoff 1991:36). This representation is identical to the analysis of inchoatives as given in (11), except that category features are replaced (Situation replaces Space, cf. Jackendoff 1991:37).

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Survey of research positions

(11) INCH ({^^ X]) ("State X comes about") =

DIMldDIR Sif

BDBY+ ([Sit X])

However arguable the representation in (11) might be, this identity of representation is nonetheless a good indication in favor of decomposition. And abstracting from the organization of motion instead of falling back onto it seems to be a better solution, which Jackendoff lastly adopts. Finally, let us consider one function more closely, which has been discussed as a predicate in Section 2.2.1., namely CAUSE. In (1972), Jackendoff holds the following view: CAUSE will be a semantic function that takes two arguments, an individual and an event; its meaning will be that the individual causes the event, in the special direct sense of 'cause' which is not accurately conveyed by the lexical item cause. (Jackendoff 1972:39)

Although starting off with a view of causation that is similar to the one McCawley began with, Jackendoff allows for an individual or an event as first and an event as second argument in (1983) (cf. also (5e) on p. 42). He accepts the analysis of other theorists (e.g., cf. Schank 1972:582-583; Miller and Johnson-Laird 1976:96-100, 113) - namely that causation is a relationship between two eventities - at least for some cases, like John's blowing bubbles make us laugh. But because of his Grammatical Constraint, which "says that one should prefer a semantic theory that explains otherwise arbitrary generalizations about the syntax and the lexicon" (Jackendoff 1983:13),61 he claims that both [THING] and [EVENT] are permissible as first argument and that the 'event-event'-relationship account does not suffice. In contrast, he emphasizes that the second argument is "an [EVENT], not a [STATE], for agents make things happen" (Jackendoff 1983: 177). That is, he restricts the range of eventities permissible as second argument to non-statal ones. We support this, because causation implies the triggering of a participant's transition. Concerning the first argument, we will follow those who favor the eventity-argument. Jackendoff himself states "that temporal expressions define a one-dimensional 'pseudospace', the well-known time-line. It is not [THINGS] that are located in time, but [EVENTS] and [STATES]" (Jackendoff 1983:189). So how can [THINGS] cause a transition without being located in time? Thus, Jackendoff himself provides the reason why we favor the analysis that causation is a relationship between two eventities. More precisely, we should

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49

say that causation is a relationship between an eventity and a transitional (or change eventity, cf. Chapter 8.) eventity, or, in his terms, between a state or event and an event. Unfortunately, his predicate dependent approach is not structured enough to enable such insights easily. With the UER's clear distinction between static and dynamic aspects of eventities, however, such results are natural conclusions. Jackendoff's Conceptual Semantics has been treated extensively, because many excellent ideas have come up during the theory's development and are present in the contemporary approach. On the other hand, this unfortunately entails that Conceptual Semantics gives the impression of being a compilation which has come into existence little by little. Following up the development, the domain which was to be described became bigger (e.g., extensions to domains other than the motional have been undertaken, or non-change eventities have been included), and it turned out that the representations had to be much more detailed than was assumed at first. For instance, selectional restrictions had to be included. It is for this reason that Jackendoff started to introduce a kind of typization in his system by adding features and subscripts to functions or including markers into constituents, which in particular characterize the participants, their relationships, and the roles they play within the eventity. Learning from this experience, we thus start off with a strongly typed language and explicit modeling elements for participants, relationships, and roles, although we also expect extensions to the UER (to account for particular verb classes, compositional semantics and the like). But the UER is a permissive system that is designed to be easily extendable.

2.2.3.

Fillmore's Frame Semantics

Whereas Jackendoff is probably the most prominent representative of the predicate dependent approach, Fillmore presumably has the corresponding status among the proponents of the predicate independent approach. Roles are basic units in Fillmore's linguistic theory (Rapp 1997:13-14), and they are considered crucial to the characterization of verbs (Petruck 1996:1). Frame Semantics, the framework on which Fillmore's current FrameNet project (Fillmore 2004; Johnson et al. 2001) is based, has been developed starting in the mid-1970s (cf. Fillmore 1976, 1977b, 1982, 1985, 1986; Fillmore and Atkins 1992; and, for a survey of the main concepts, Petruck 1996). It "is a research program in empirical semantics which emphasizes the conti-

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Survey of research positions

nuities between language and experience" (Petruck 1996:1). The central notion, the frame,62 is understood as any system of concepts related in such a way that to understand any one of them you have to understand the whole structure in which it fits; when one of the things in such a structure is introduced into a text, or into a conversation, all of the others are automatically made available. (Fillmore 1982: 111)

A frame is thus a comprehensive collection of concepts linked to each other. It is the underlying conceptual structures of a specific, delimited conceptual region. From a lexical semantics point of view, it can be seen as the background against which words are defined.63 Unlike in lexical field theories, a word is not defined in relation to other words, but in relation to this conceptual background.64 Consider as an example of a frame the often-cited Commercial Transaction Frame, whose frame elements (a notion equivalent to a refined notion of semantic roles, cf. Boas 2001:64; Fillmore 2001, and below)65 include a buyer, seller, goods, and money: Among the large set of semantically related verbs linked to this frame are buy, sell, pay, spend, cost, and charge, each of which indexes or evokes different aspects of the frame. The verb buy focuses on the buyer and the goods, backgrounding the seller and the money; sell focuses on the seller and the goods, backgrounding the buyer and the money; pay focuses on the buyer, the money, and the seller, backgrounding the goods; and so on. The idea is that knowing the meaning of any one of these verbs requires knowing what takes place in a commercial transaction and knowing the meaning of any one verb means, in some sense, knowing the meaning of all of them. The knowledge and experience structured by the Commercial Transaction Frame provide the background and motivation for the categories represented by the words. (Petruck 1996:1)

Thus, in understanding frames as experience-based schematizations, an account of the meaning of a lexical item (and therefore a verb as the focus of our investigation) is assumed to "proceed from the underlying semantic frame to a characterization of the manner in which the item in question, through the linguistic structures that are built up around it, selects and highlights aspects or instances ofthat frame" (Johnson et al. 2001: 11). Hence, in Frame Semantics the semantics of lexical items are highlighted conceptual structures. In the UER, the approach is similar: semantics is conceived of as conceptual structures that are carved out and constitute a conceptual unit. However, the UER

Approaches to decompositional semantics

51

does not assume a frame as a bounded conceptual background, in the context of which the highlighting takes place. Instead, UER EVENTITY FRAMES reflect the conceptual units which are carved out and hence the highlighted structures themselves. Most of the frames described in the FrameNet project occur in quite specific domains: [F]rames in the FrameNet project are organized by domain, which are very general categories of human experience and knowledge. Domains serve as useful groupings of semantic frames, but their theoretical significance is slight and indirect. (Johnson et al. 2001:16)

The domains are body, cognition, communication, emotion, general, health, life, motion, perception, society, space, time, and transaction. There are, however, some frames of a very general nature, whose characteristics more specific frames inherit, and in some cases entire domains inherit (for example, the Communication Frame is such a general frame). These higher-level frames are considered to characterize the basic structural properties of events and relations in the more specific frames (Johnson et al. 2001:73). In what respect can Frame Semantics be considered decompositional? The 'dynamicity' of the described eventities, that is, their course of events, is at best mentioned in the non-decompositional frame descriptions. Compare the frame description of the Commercial Transaction Frame: General Description These are verbs describing basic commercial transactions involving a buyer and a seller exchanging money and goods. The words vary individually in the patterns of frame element realization they allow. (Johnson et al. 2001:188)

This is further elaborated on: The commercial transaction frame involves such concepts as possession, change of possession (giving, taking/receiving), exchange (the parties in the exchange accept and are expected by their community to accept the results of the exchange), and money (an artefact which the culture has dedicated to the purpose of exchange and which has no other function). The basic frame elements, then, will include Money, the Goods (standing for goods or services), the Buyer (the person who surrenders money in exchange for the goods), and the Seller (the person who surrenders the goods in exchange for the money). (Johnson et al. 2001:12)

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Nevertheless, there is some 'predicate independent decompositionality' in the set of frame elements which is depicted for each frame (as partly elaborated on in the latter citation). The frame elements enumerate the participants or semantic roles in potential eventities falling within the range of the frame in question. For the Commercial Transaction Frame they are listed in Table 3. Table 3. Frame elements of the Commercial Transaction Frame (Johnson et al. 2001:188) Frame element

Example (in italics)

Buyer Seller Payment66 Goods Rate Unit

Pat bought a new guitar. Pat bought a guitaryrom Kim. Kim sold the guitar for $250. Kim sold the guitar for $250. The plumber charges $20 an hour. The plumber charges by the hour.

For each frame its frame elements are specified, which results in dozens of different participant role names. Frame elements are generally not comparable to each other, because they are conceived of as basic units - any properties they entail are, if at all, only discussed rudimentarily. Yet, the inheritance structure that is imposed on the frames might entail a hierarchical order of roles and relate the roles to each other. Probably many of the roles are children of other, more general roles. Frame element names, in other words role names, often indicate the frame to which the frame elements belong and are not independent from the particular frame: Seller, Buyer and Goods are frame elements of the Commercial Transaction Frame, Communicator, Addressee and Message are the corresponding, but differently termed frame elements of the Communication Frame. That way no comparison between the frame elements is possible. Moreover, characteristics of the meaning carried by the frame (such that the frame is a frame describing commercial transaction or communication) are encoded in the role descriptions, information that in our opinion should not be present in role notions. In contrast to Frame Semantics, we thus propose a set of feature-based abstract roles for the UER (cf. Section 6.6.). Although a realization of roles along the lines of FrameNet would in principle be possible in the UER, we prefer a system in which - as indicated before - semantic roles reflect prominent configurations. In order to align those configurations to the respective

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eventities, their properties can, however, be overwritten or supplemented by role-ATTRIBUTES in the modeling. The concept of inheritance, which is in principle available for all modeling elements in the UER (cf. the GENERALIZATION concept in Sections 4.2.10. and 6.8.), is specifically defined for frames in FrameNet. Frame inheritance is specified as a relation between two frames such that one of them has all the properties of the other, plus additional characteristics. In the frame database, semantic generalizations across frames are captured through the abstraction of general frames and the inheritance of these frames by more specific ones. In the resulting inheritance lattice, it is generally true that each domain contains one general frame that captures what the more specific frames in that domain have in common. In this respect domains do have a degree of theoretical significance - they are broad-level generalizations over the frame network that we are constructing. (Johnson et al. 2001:16)

Moreover, FrameNet allows for frame blending, which corresponds to 'multigeneralization' in the UER. For example, particular words belong simultaneously to a Conversation Frame and a Dispute Frame (e.g., fight). Interestingly, these two frames themselves involve a blend between an abstract Reciprocity Frame - operating in many domains - and speaking and assailing, respectively (cf. Johnson et al. 2001:59). The specification of lexical items is handled as follows:67 "A frame semantic description of a lexical item identifies the frames which underlie a given meaning and specifies the ways in which FEs [frame elements], and constellations of FEs, are realized in structures headed by the word" (Johnson et al. 2001:9). A complete description of a verb includes information about their grammatical properties and the various syntactic patterns in which it occurs (Petruck 1996:1). For instance, for the Commercial Transaction Frame the following "typical patterns" for English buy and sell are suggested: BUYER buys GOODS from SELLER for PAYMENT SELLER sells GOODS to BUYER for PAYMENT (Johnson et al. 2001:188)

By enumerating all possible syntactic patterns, a distinction between obligatory and optional arguments is not enforced and not possible. Transferring this to participants and correspondingly semantic roles, this entails

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that one cannot distinguish between participants which are necessary when describing a verb's semantics and those which might additionally be specified and modify the eventity in question. For example, German wecken 'wake up' requires solely an actor and an undergoer, but e.g., no manner to be specified. By disregarding the necessity for distinguishing obligatory and optional elements, the variety of patterns to be investigated reaches an oversized number. In effect, FrameNet can be said to list a set of syntactic patterns on the basis of which frame elements are established, but not to entail a genuinely semantic representation of lexical items. In particular, neither is the course of events represented nor are other characteristics included that are inherent to verbal meaning, such as selectional restrictions. Both the dynamic structure that is in the center of UER semantic modeling of verbs (as indicated by the notion of dynamic core, cf. Section 5.4.1.) and the specification of distinguishing characteristics are not accounted for in FrameNet. Compare, for example, the representations of walk and accompany in (12), referring to the sense as expressed there (Boas 2001 : 70). The difference in meaning between walk and accompany is not explicated but left implicit: (12) a. Rod walked Melissa to the door. [Self-mover Cotheme Goal] b. Rod accompanied Melissa to the door. accompany cotheme [Self-mover Cotheme Goal] Final critical remarks on the conception that speakers "can be said to know the meaning of a word only by first understanding the background frames that motivate the concept that the word encodes" (Fillmore and Atkins 1992: 77) seem apposite. In our view, knowing the meaning of buy or sell, to stay with the example of the Commercial Transaction Frame, does not necessarily require the knowledge of frame elements like Rate or Unit. This might be covered by the theory in dubbing particular frame elements as "essential props and players in any commercial event scene" (Fillmore and Atkins 1992: 78). In the case of the Commerical Transaction Frame, the essential players would probably be Buyer, Seller, Goods, and Payment. But unfortunately, there is no precise notion of essential players, nor is this notion systematically used and applied in the FrameNet framework. Relating to this, another question arises concerning conceptualization (cf. also Chapter 7., and in particular Section 7.3.). Is, e.g., the seller of a BUYeventity necessarily co-conceptualized and present in the conceptualization

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of the BUY-eventity, though backgrounded and unspecified (since the seller is not explicated in the linguistic realization of the BUY-eventity)? We are inclined to reject this. This leads us to the problem of clearly differentiating between 'logically' existing participants of an eventity and those that are in addition present in a conceptualization of the eventity in question. Our world knowledge might tell us that some participants have to exist in some way, but they are not necessarily highlighted in the semantics, i.e., not conceptualized and hence not present in the semantic representation. Indeed, the seller, whether it is a selling machine or a human seller, has to exist, but is not conceptualized as participant of the BUY-eventity, and therefore should not be present in a representation of buy.

2.2.4.

Wunderlich's Lexical Decomposition Grammar

The Lexical Decomposition Grammar (LOG, cf., Wunderlich 1996b, 1997) is based on the Two-Level Semantics advocated by Bierwisch, Lang and their followers (cf., e.g., Bierwisch 1982, 1983; Bierwisch and Lang 1987b; Bierwisch and Schreuder 1992). The name of the Two-Level Semantics indicates that it distinguishes between two levels of representation, namely the semantic form (SF) and the conceptual structure (CS). The "SF is considered a computational level of grammar, and CS is the level of reasoning that may draw on any kind of mental operations" (Wunderlich 1997:29). The SF is part of the grammar and is considered to be the interface level between syntax/morphology and conceptual structure (Wunderlich 1996b: 169). More precisely, it is "a grammatical level at which complex verbs are minimally decomposed into more basic predicates" (Wunderlich 1997:27). Wunderlich concludes that lexical decomposition in terms of the SF, therefore, need not go beyond a certain granularity. Proponents of Two-Level Semantics and LDG work on the assumption that the SF is a predicate-argument representation of the invariant semantic components of lexical items, of components represented in a lexical entry. The components are part of a representation which may be compared to the logical structure or logical form extended to sublexical structures (Wunderlich 1997:29), cf. Example (13). In particular, the SF of lexical entries generally comprises free variables or parameters which are bound in the final context-dependent semantic interpretation of the CS. (13) empty: CAUSE (x, BECOME (EMPTY(y))) (s)

(Wunderlich 1997: 36)

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Interestingly, there is no elaborated theory of the representation of the CS to date. Wunderlich calls it a "more elaborated semantic representation" (Wunderlich 2000:254) than the SF. The CS is to include information on implicit arguments, sortal restrictions, thematic roles, temporal/clausal structure, subevents, and the like (Wunderlich 2000:254). The UER could be understood as a means or metalanguage to obtain CS-like representations, since it embraces mechanisms to account for such information. Yet we do not assume two levels in the representation and will not commit ourselves to a fixed number of levels. Within our approach, verbal meaning can be displayed as a highly structured, content-rich cluster of conceptual elements. It can be understood either as a one-level representation or as a multi-level representation with different substructures and modeling regions within the representation establishing different levels. These can be seen to correlate with different degrees of granularity and explicitness. However, the lack of a clear conception of the CS in Two-Level Semantics entails that the SF cannot be deduced from this at best sketchily represented but "rich conceptual structure" (Wunderlich 1997:30).68 By modeling with the UER, we hope to be able to deduce particular grammatically relevant reflexes from the rich UER representations, although this does not fall within the scope of the present work and has to be postponed to future research efforts. Wunderlich imposes an important assumption on the SF, namely "the minimalist assumption of SF structures, by which only those aspects of meaning that are relevant for syntactic properties should be captured in SF" (Wunderlich 1996b: 170). This corresponds to his conception of lexical decomposition. "Lexical decomposition aims at a characterization of sublexical structure in so far as it determines the grammatical properties of lexical items" (Wunderlich 1996b: 169).69 Of course, such an approach is not tenable if we aim at providing a representational framework for verbal semantics (as is the case with the UER), where the focus lies on representing meaning rather than grasping grammatical properties. Thus, we pursue a different aim with the UER than Wunderlich's approach does. Accordingly, we will start from the opposite, with a rich semantic representation, abstractions of which might enable the deduction of grammatical properties. Causation plays a crucial role in Wunderlich's considerations. In particular, he distinguishes between 'explicit' and 'implicit' causative verbs: It is important to notice that a distinction is being made between verbs that only express the result of an activity and those that in addition ex-

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press a particular kind of activity. The former are represented explicitly with CAUSE, whereas the latter encode the causal interpretation implicitly. (Wunderlich 1997:57-58)

Compare his example (Wunderlich 1997:58), the representation of machen 'make' versus backen 'bake', in (14). (14) a. machen: CAUSE (x, BECOME (EXlST(y))) (s) b. backen: (BAKE(x) & BECOME (EXIST(y))} (s) The difference in representation is not directly comprehensible, since Wunderlich himself states that the semantic difference only amounts to the expression of the kind of "activity" which is inherent in (14b) but not in (14a). The resulting substantially different representations contradict intuitions about the semantic difference. In addition, Wunderlich in particular argues against McCawley's DO predicate, because in his opinion it does not allow the derivation of any syntactic or aspectual effects: "Languages simply do not exploit this conceptual possibility; therefore, the SF of causative verbs should abstract away from any properties of the causing situation except the existence of an agent or causer entity" (Wunderlich 1997:36), as shown in (14a). Even if one follows his argumentation up to this point, the problem of appropriately interpreting the conjunction in (14b) (namely as expressing causation) arises. This is achieved by a general coherence constraint that was originally initiated by Kaufmann70 and states that subeventities are interpreted as being causally related, or, in Wunderlich's terms: a "lexical SF conjunction is contemporaneously or causally interpreted" (Wunderlich 1997:36). The coherence constraint is then considered to enforce the causal interpretation in (14b), as the predicate BECOME (which seems to indicate a non-durative transition for Wunderlich) is contained in the representation, together with a process predicate: [E]very verb (basic or extended) refers to a coherent situation that has to be individuated in time. A verb refers either to something that happens in a particular time interval or to something connected by a causal chain. If the verb is represented by a conjunction in SF, the conjoined propositions may be predicated of the same time interval and thus be understood as contemporaneous, or they may be predicated of different subintervals if they are causally related. The latter option is required whenever the representation contains the predicate BECOME as a conjunct, together with a process predicate. (Wunderlich 1997:36)

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Firstly, this is questionable because an interpretation of whether particular predicates represent processes or not becomes necessary. That is, even if we assign the predicate BECOME a defined and specified status in (14b), we still have to find out whether BAKE is a process predicate or not. Secondly, the interpretation of a non-processural action in conjunction with BECOME is ambiguous. How are we to decide whether the subeventities are contemporaneous or causally related in such a case? Moreover, verbs encoding subeventity sequences such as FETCH (which is encoded in some languages by serial verb constructions, but in other languages by one lexeme, cf. Schalley 2003b, and which does not exhibit explicit causal relations) cannot be captured by the SF. Thus, the LDG's SF does not provide appropriate representation mechanisms. Its representation is not as intuitive and consistent as desirable. In particular, an adequate mechanism for the representation of temporal and causal structure and their distinction is not available. This is clearly distinguished in the UER, where temporal structure is represented by the course of a statetransition system and causation is explicitly modeled by the cause-SiGNAL (cf. Section 6.10.). Nevertheless, the coherence constraint rightly prohibits particular SFs as representations for verbal semantics (cf. also the discussion in Section 7.1.). One such SF is *[P(x) & Q(y)], with x^y, P^Q, examples of which are given in (15) (Kaufmann 1995:198-199). (15) a. *[BANG(x) & GLOW(y)] b. *[BECOME (LIQUID(x)) & BECOME (FULL(y))]

For further work in and on the LOG, including aspects which have not been touched on in this brief discussion, cf., amongst others, Stiebels 2000 (who uses LOG in terms of Correspondence Theory, an offspring of Optimality Theory) and Wunderlich (1996a, 1996b, 2000). Cf. Wunderlich (1996b) for a comparison of LOG (and from the LDG's perspective) to Jackendoff's and Pustejovsky's approaches which are discussed in the Sections 2.2.2. and 2.2.5.

2.2.5.

Pustejovsky's Generative Lexicon

As mentioned in Section 2.1.3.2., Pustejovsky views the lexicon as being highly organized and equipped with a remarkable degree of systematicity and generativity. This view is reflected in his Generative Lexi-

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con approach, which is designed to dynamically capture regular polysemy (Pustejovsky 199la: 409). Pustejovsky emphasizes the creative aspect of the lexicon and aims at avoiding a 'sense enumeration stategy':71 I will show that there are three basic arguments showing the inadequacies of SELs [sense enumeration lexicons] for the semantic description of language. (1) THE CREATIVE USE OF WORDS: Words assume new senses in novel contexts. (2) THE PERMEABILITY OF WORD SENSES: Word senses are not atomic definitions but overlap and make reference to other senses of the word. (3) THE EXPRESSION OF MULTIPLE SYNTACTIC FORMS: A single word sense can have multiple syntactic realization[s], (Pustejovsky 1995:39) Evidently, Pustejovsky advocates decompositionality (cf. the second argument). He strives to minimally decompose lexical items "into structured forms (or templates) rather than sets of features" (Pustejovsky 1991b:52), but he approaches lexical semantics differently than Wunderlich. Although he pays much attention to compositionality and to the relation between semantic and syntactic structure - two aspects which are not in our focus but treated extensively by Wunderlich - he nevertheless takes a view which is also supported in our approach: [T]he meanings of words should somehow reflect the deeper conceptual structures in the cognitive system, and the domain it operates in. This is tantamount to stating that the semantics of natural language should be the image of nonlinguistic conceptual organizing principles, whatever their structure. (Pustejovsky 1995:6) However, the UER is in a sense fundamentally different from the Generative Lexicon. We propose a different account of capturing conceptual structures than other linguistic approaches, including Pustejovsky's, have done to date. Our approach is graphical and object-oriented. More precisely, the UER borrows from a quite intuitive modeling language for the design of object-oriented systems, the UML. Our belief that an object-oriented approach suggests itself is supported by Pustejovsky's following observation: "When we combine the qualia structure of a NP with the argument structure of a verb, we begin to see a richer notion of compositionality emerging, one that looks very much like object-oriented approaches to programming"

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(Pustejovsky 199la: 427). However, he does not draw the obvious conclusion from this observation, namely to draw on insights gained in computer science on object-orientation, as is done with the UER. In another respect, our approach is similar to Pustejovsky's decompositional approach: both are not restricted to merely capturing those aspects of meaning that are relevant for syntactic properties, as Wunderlich's SF is. Instead, Pustejovsky's focus lies on representing semantics as such, and he develops "the idea of a lexicon in which senses in context can be flexibly derived on the basis of a rich multilevel representation and generative devices" (Behrens 1998:108). The generative devices he proposes are type coercion (probably the most important), selective binding, and co-composition (Pustejovsky 1995:61). But since they play a role in compositional semantics, they are not discussed here.72 The multilevel representation that specifies lexical items consists of four prime levels, namely argument structure, event structure, qualia structure, and lexical inheritance structure. The argument structure entails a specification of the number and types of the logical arguments, and how they are realized syntactically. The event structure defines the event type (including state, process, and transition; events may have subeventual structure, cf. Pustejovsky 1995:61). The qualia structure comprises "modes of explanation" (Pustejovsky 1995:61) and is composed of formal, constitutive, telic, and agentive roles. Finally, the lexical inheritance structure identifies "how a lexical structure is related to other structures in the dictionary, however it is constructed" (Pustejovsky 1995:58). Note that Pustejovsky does not display lexical inheritance structures in his semantic representations, although he touches on it in Chapter 8 of Pustejovsky (1995). Hence, lexical inheritance structure (entailing the structural relations in the lexicon) will not be introduced in the following, whereas the other three structures will be presented. The argument structure for a word can be seen as a minimal specification of its lexical semantics. By itself, it is certainly inadequate for capturing the semantic characterization of a lexical item, but it is a necessary component. (Pustejovsky 1995:63) Pustejovsky (1995:63-64) distinguishes four types of arguments for lexical items: - true arguments (syntactically realized parameters of lexical items, e.g. John arrived late)',

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- default arguments (parameters which participate in the logical expressions in the qualia, but which are not necessarily expressed syntactically, e.g., John built the house out of bricks); - shadow arguments (parameters which are semantically incorporated into the lexical item; they are considered to be expressed only by operations of subtyping or discourse specification, e.g., Mary buttered her toast with an expensive butter); and - true adjuncts (parameters which modify the logical expression, but are part of the situational interpretation, and are not tied to any particular lexical item's semantic representation, e.g., Mary drove to New York on Sunday).13

Questions of syntactic realization and true adjuncts are of no relevance for the current state and aim of the UER, since we do not deal with situational interpretations, but restrict ourselves to semantic representations of verbs. In fact, our approach will be exclusively semantic right from the start - we will look at participants playing a role in the eventity that is encoded by a particular verb. Questions of linking or shadowing, adjuncts and the like are left out of consideration, but they are elements that will be potentially integrated in the UER framework in future work.74 However, we would expect that default arguments, which seem to be comparable to Fillmore's non-essential frame elements, are not conceptualized and hence should not be entailed in the representation of a verb's meaning. Pustejovsky's argument structure is represented by a list structure, with characteristics of the arguments being explicitly encoded, that is, the selectional restrictions of the eventity's participants are represented. The partial semantic representation that displays the argument structure of build is given in (16), following Pustejovsky's proposal (Pustejovsky 1995:67) (where DARG is a default argument): buUd

(16)

ARGSTR=

ARG i = animate Jndividual ARG2 = artifact D-ARG ι = material

Pustejovsky captures the internal structure of eventities with his event structure. Besides being one of the four levels of the semantic specification of a lexical item, the event structure is one of three levels he assumes for representing the structure of verbal semantics. The event structure is the first level,

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the level on which event types are attributed to the verbs (event types can be primitive or complex, cf. below). The second level is the LCS'-level, which outlines a minimal decomposition of verbs in terms of the principles of the event structure. The parts of the LCS'-level are connected to the event types shown in the event structure. The third level is the so-called LCS-level, where Pustejovsky uses, like Jackendoff (1983, 1987, 1990; cf. also Section 2.2.2.), a lexical conceptual structure. The LCS-level gives representations of lexical semantics in the form of predicate decomposition. Pustejovky (1991b: 57) considers the LCS-representation to be constructable by interpreting the event structure together with the LCS'-level. In other words, he tries to construct a derivation mechanism for the well-known predicate decomposition. Of particular interest in the following is thus the event structure and its linking to the LCS'-level. Cf. Example (17) with the corresponding representation of its event decomposition in Figure 3. (17) John closed the door. (Pustejovsky 1991b: 58) ES:

LCS': [act(j, the-door) &-> closed(the-door)] LCS:

[closed(the-door)]

cause([act(j, the-door)], become([closed(the-door)]))

Figure 3. Example of event decomposition (Pustejovsky)

According to Pustejovsky, any verb in natural language can be characterized as belonging to one of three basic event types state, process, or transition (Pustejovsky 1991b:55-56).75 In the example in Figure 3, we are dealing with a transition (cf. T in the representation). A transition is fuzzily defined as "an event identifying a semantic expression, which is evaluated relative to its opposition" (Pustejovsky 1991b: 56). Its structural representation is given in Figure 4 (E is a variable for any event type). Note that no opposition is apparent from the representation (generally, ->E2 is not the opposite of £1). As becomes obvious in Figure 3, the opposition can be understood as an opposition between the resultant state ->E2, closed (the-door), of the transition

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and its opposite (which is - not in all cases, but in the example - a proper part of £1). Thus, either the opposite of ->E2 is part of a conjunction76 £1, or E1 equals E2. The respective notations of the other two basic event types are also given in Figure 4. A state in Pustejovsky's terms is a single event (e), which is evaluated relative to no other event. A process "is a sequence of events identifying the same semantic expression" (Pustejovsky 1991b:56), i.e., consists of a sequence of events that in sum make up a process. Thus, the event types constituting the transition in the example in Figure 3 are, following Pustejovsky, process (P) and state (5) (although the process entails a further state, namely ->closed(the-door), which is not considered in the representation). State

e

Process

el

...

Transition

en

El

~i(E2)

Figure 4. Basic event types (Pustejovsky)

Generally, event types can be primitive (i.e., basic) or complex. A complex event type e, in the event structure denoted as [e\ €2], is interpreted as an event with two subevents, where the first temporally precedes the second (cf. Pustejovsky 1991b: 56). Overlaps and inclusion of subevents are possible in the 'extended event structure', representing the relation between an event and its proper subevents. For a discussion, cf. Pustejovsky (1995:67-75) and Pustejovsky and Bouillon (1996:140-141).77 Since the subevents of an event need not to be primitive themselves, Pustejovsky establishes a binary tree structure to represent events (cf. Pustejovsky 2000a: 453, Tenny and Pustejovsky 2000a: 11). In the semantic specification of a lexical item (which is itself a list), the event structure is again depicted as a list, entailing "the specific events and their types; and the ordering restriction over these events" (Pustejovsky 1995:71) (notated as RESTR in the list). For the case of build, the event structure part of the lexical entry then results in (18), where build is analyzed as involving a process followed by a resultant state and ordered by the relation " 'exhaustive ordered part of,'

«meronomy»

Figure 10. Varieties of STEREOTYPE notation

Relevance Clusters of recurring characteristics which describe subsets or subtypes (cf. Section 6.13.). Stereotype Declaration A STEREOTYPE is defined using the CLASS notation (cf. Section 4.2.1.), a rectangle, with the keyword «stereotype».98 The name of the STEREOTYPE is placed in the upper of the two compartments (for the specification of the compartments, cf. Section 4.2.1.) which are separated by a horizontal line (cf. 3-58). CONSTRAINTS and PROPERTY definitions" of elements described by the STEREOTYPE may be placed in the lower compartment, which also may be split up into two named compartments called Constraints and Properties (cf. 3-58). Specifically, it is necessary to show how the STEREOTYPE relates to its base element. This is denoted using a STEREOTYPE also called «stereotype» which is attached to a DEPENDENCY (cf. Section 4.2.11.) between the STEREOTYPE definition and the base element (where the arrow head connects to). Example Figure 11 shows the declaration of the «meronomy» STEREOTYPE: the PROPERTIES that can and CONSTRAINTS that have to apply to MERONOMY relations are listed in the lower compartment (for an explanation of these, cf. Section 5.1.1.). The base element of MERONOMY is AGGREGATION, that is, MERONOMY is a subtype of the AGGREGATION relation (cf. Section 5.1.

94

Basic concepts of the U ER «metaclass» Aggregation «stereotype»

«stereotype» Meronomy Properties

propagation: Enumeration control: Enumeration isConfigurational: Boolean isEncapsulated: Boolean isExchangeable : Boolean isFunctional: Boolean isHomeomerous: Boolean isHomogeneous: Boolean isMandatory: Boolean isNecessary: Boolean isRemovable: Boolean isSegmental: Boolean isSeparable: Boolean isShareable: Boolean Constraints

{The whole has more than one proper part at the instance level.} {The aggregate is conceptualized as unity.} {The whole has an independent ontological existence (which transcends its parts).} {The whole has (at least) an emergent property.} {The whole has (at least) a resultant property.} {Antisymmetry holds at the type level.} Figure 11. Notational form for declaring STEREOTYPES

4.1.5.

Enumeration

An ENUMERATION is a user-defined data type100 whose instances are a set of user-specified named values or identifiers, the so-called ENUMERATION literals (cf. 3-57). Any ENUMERATION is a primitive data type, where the values (that are, for example, used as the range of a particular ATTRIBUTE type) are listed in the definition of the respective ENUMERATION. Notation An ENUMERATION is defined using the CLASS notation (a rectangle) with the keyword «enumeration». The name of the ENUMERATION is placed in the upper of the two compartments which are separated by a horizontal line. Above the name the keyword «enumeration» is placed. An

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ordered list of ENUMERATION literals is placed, one to a line, in the lower compartment (cf. 3-57). Example Figure 12 displays the ENUMERATION PlaceOf Articulation that comprises as ENUMERATION literals the different places of articulation that are usually used for phonological descriptions. In a sense, the definition of this ENUMERATION is a prerequisite to the modeling given in Figure 8 on p. 86 in the previous chapter, because it specifies the type of the ATTRIBUTE place which would otherwise remain undefined. «enumeration» PlaceOf Articulation bilabial labiodental dental

alveolar postalveolar retroflex palatal velar

uvular pharyngeal laryngeal

Figure 12. ENUMERATION Relevance Recurring cognitive categories specified by lists of values and, for instance deployed in the specification of ATTRIBUTE types (cf. also Section 6.2.). 4.2.

Static structure concepts

Static structure concepts are concepts that typically model ineventities as represented by OBJECTS or CLASSES (cf. Section 6.5.), their internal structure and characteristics (e.g. ATTRIBUTES), and their relationships to other entities (e.g. LINKS or ASSOCIATIONS, GENERALIZATIONS). Static structure modeling does not overtly show temporal information, although reified occurrences of entities that have or describe temporal behavior may be contained (cf. 334). This section discusses CLASSES and their variations, the relationships between CLASSES, and the contents of CLASSES. Of course, the type-instance dichotomy between CLASSES and OBJECTS will be accounted for as well.

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4.2.1.

Class

"A CLASS is the descriptor for a set of OBJECTS with similar structure, behavior, and relationships" (3-35) and thus a model element on the type level. "The model is concerned with describing the intension of the CLASS, that is, the rules that define it" (3-35). The extension of a CLASS are its instances, that is, its OBJECTS (cf. Section 4.2.3.). The UER provides notation for declaring CLASSES and specifying their properties (depicted as ATTRIBUTES), as well as using CLASSES in various ways.101 Some modeling elements that are similar in form to CLASSES (such as ENUMERATION types and SIGNALS, cf. Sections 4.1.5. and 4.3.8.) are notated using keywords on CLASS symbols (cf. 3-35). Notation "A CLASS is drawn as a solid-outline rectangle" (3-36) with basically two compartments separated by a solid horizontal line. The top name compartment holds the CLASS name and possibly STEREOTYPES (cf. 3-36); the other compartment holds lists of different kinds of ATTRIBUTES, optionally in different sub-compartments. Each sub-compartment is separated by horizontal lines as well. Either of the sub-compartments or the whole ATTRIBUTE compartment may be suppressed. A separator line is not drawn for a missing (sub-) compartment. Sub-compartment names can be used for clarification or to remove ambiguity, if necessary. They are displayed in a distinctive font centered at the top of the sub-compartment (cf. 3-39).102 This capability is useful if some sub-compartment is omitted. Name Compartment The obligatory name compartment displays the name of the CLASS and, if necessary, a STEREOTYPE or keyword. If there is a STEREOTYPE or keyword, it is placed above the CLASS name within guillemets, and the name of the CLASS appears below. If the CLASS has the PROPERTY {abstract}, its name appears in italics, or the PROPERTY is placed in a PROPERTY list below or after the name (cf. 3-38). List (Sub-) Compartment A list (sub-) compartment, such as the ATTRIBUTE compartment or its sub-compartments, "holds a list of strings, each of which is the encoded representation of a feature" (3-38), such as an ATTRIBUTE. The strings are presented one to a line (cf. 3-38). The items in the list are ordered. An ellipsis ('...') "as the final element of a list or the final element of a delimited section of a list indicates that additional elements in the model exist that meet the selection condition, but that they

Static structure concepts

97

are not shown in that list" (3-39). A keyword (including STEREOTYPES) or PROPERTY string may be shown as an element of the list, in which case it applies to all of the succeeding list elements until another keyword or PROPERTY string appears as a list element or an empty keyword or PROPERTY string («», { }) nullifies the previous string. This is equivalent to attaching the keyword or PROPERTY string to each of the list elements individually (cf. 3-39).

Consonant

Consonant place: PlaceOfArticulation manner: MannerOfArticulation isVoiced: Boolean

Figure 13. CLASS

Examples Figure 13 displays two variants of CLASS notation. The first one shows the CLASS of all consonants with suppressed list compartment: only the name of the CLASS is shown. The second one also comprises the list compartment. The list of ATTRIBUTES names properties or characteristics members or instances of the CLASS will provide a value for (for a similar example, cf. Figure 8 on p. 86). Figure 14 takes up Figure 12, but this time the list elements are further categorized by STEREOTYPES. »enumeration» PlaceOfArticulation

«labial» bilabial labiodental «coronal» dental alveolar postalveolar retroflex «dorsal» velar uvular «radical» pharyngeal

Figure 14. STEREOTYPES applied to groups of list elements

98

Basic concepts of the UER

Relevance

4.2.2.

Categories with members or instances (cf. Section 6.4.).

Attribute

"Strings in the ATTRIBUTE compartment are used to show ATTRIBUTES in CLASSES" (3-41). An ATTRIBUTE is a named slot within a CLASS that describes a range of values instances of the CLASS may hold (cf. 2-24). Notation "An ATTRIBUTE is shown as a text string that can be parsed into the various properties of an ATTRIBUTE model element" (3-42). The default syntax is: name ':' type-expression '[''multiplicity1]' '=' value-expression '{'property-string''}' In this text string (cf. also 2-24, 3-42-3-43): - name is an identifier string that represents the ATTRIBUTE'S name. - type-expression designates the data type whose elements are values of the ATTRIBUTE. Only primitive data types such as Integer, Real (i.e., number types), Boolean, and other ENUMERATION types are allowed.103 The type expression may be suppressed (but it has a value in the model). - multiplicity shows the MULTIPLICITY (cf. Section 4.2.6.) of the ATTRIBUTE, that is, the possible number of data values for the ATTRIBUTE that may be held by an instance. In the common case in which the MULTIPLICITY is 1..1, the ATTRIBUTE is a scalar (i.e., holds exactly one value), and the term may be omitted.104 - value-expression is an expression specifying the value of the ATTRIBUTE. That is, if a value for an ATTRIBUTE is depicted in a CLASS specification, then each instance of this class has to have this value. This is not to say that the value may not be modified afterwards, but for instances to be participants of the modeled eventity it has to hold within the eventity. If the value displays an intrinsic characteristic of the instances and thus may not be changed, the STEREOTYPE «intrinsic» is to be enclosed in front of the ATTRIBUTE name. If the value-expression is suppressed, the value is absent from the model, that is, each instance of the CLASS has an ATTRIBUTE of this type (unless null values are possible), but the values may differ from one another.105 — property-string indicates PROPERTY values that apply to the element. The PROPERTY string is optional (the braces are omitted if no PROPERTIES are specified).

Static structure concepts

99

"A STEREOTYPE keyword in guillemets precedes the entire ATTRIBUTE string. ... A PROPERTY list in braces follows the rest of the ATTRIBUTE string" (3-43). Examples

The following examples show variants of ATTRIBUTE notation: «intrinsio ani : Animacy = human ani = animate islntentional : Boolean = true isVolitional = false colors : Color [3]

Relevance Semantic features, selectional restrictions, refinement of semantic roles (cf. Section 6.3.).

4.2.3.

Object

"An OBJECT represents a particular instance of a CLASS" (3-64), it is structured and behaves according to its CLASS. It has identity and ATTRIBUTE values (cf. 3-64). "All OBJECTS originating from the same CLASS are structured in the same way. ... An OBJECT may have multiple CLASSES; that is, it may originate from several CLASSES. In this case, the OBJECT will have all the features declared in all of these CLASSES, both the structural and the behavioral ones. Moreover, the set of CLASSES; that is, the set of features that the OBJECT conforms to may vary over time. New CLASSES may be added to the OBJECT and old ones may be detached" (2-113). This means that the features of the new CLASSES are added to the OBJECT, and the features declared in a CLASS which is removed from the OBJECT are removed from the OBJECT. Notation The OBJECT notation is derived from the CLASS notation by underlining instance-level elements, as explained in Section 3.4. "An OBJECT is shown as a rectangle with two compartments. The top compartment shows the name of the OBJECT and its CLASS, all underlined" (3-64-3-65), using the syntax: objectname ':' class-name "The name of the OBJECT may be omitted. In this case, the colon should be kept with the CLASS name. This represents an anonymous OBJECT of the

100 Basic concepts of the UER given CLASS given identity by its relationships. The CLASS of the OBJECT may be suppressed (together with the colon)" (3-65), with only the name of the OBJECT being present. "A STEREOTYPE for the CLASS may be shown textually (in guillemets above the name string). ... The STEREOTYPE for an OBJECT must match the STEREOTYPE for its CLASS" (3-65). "To show multiple CLASSES that the OBJECT is an instance of, use a comma-separated list of CLASS-names. To show the presence of an OBJECT in a particular STATE [cf. Section 4.3.1. ] of a CLASS, use the syntax: objectname ':' class-name '[' slatename-list']' The list must be a comma-separated list of names of STATES that can legally occur concurrently. The second compartment shows the ATTRIBUTES for the OBJECT and their values as a list. Each value line has the syntax: attributename ':' type '=' value The type is redundant with the ATTRIBUTE declaration in the CLASS and may be omitted. ... ATTRIBUTES whose values are not of interest may be suppressed" (3-65). The ATTRIBUTE value compartment as a whole may be suppressed (cf. 3-65). The^ow relationship between two values of the same OBJECT over time can be shown by connecting two OBJECT symbols by a dashed arrow with the STEREOTYPE «become» (cf. 3-65). Example Figure 15 shows the same OBJECT, Anna, of the type Person. The notational form of the expression in the name compartment differs but is in accordance with the possible varieties of the name notation given above. The two OBJECT symbols are connected by a flow relationship (as indicated by «become»). The value of one ATTRIBUTE of Anna's specification changes over time according to the representation, namely from non-adult to adult, i.e., from isAdult = false to isAdult = true. Anna

Anna : Person

isFemale : Boolean = true isAdult: Boolean = false hairColor: Color = black

«become·

Figure 15. OBJECT (with flow relationship)

isFemale : Boolean = true isAdult: Boolean = true hairColor: Color = black

Static structure concepts

101

Relevance Members or instances of categories represented by CLASSES, entities Out there in the world'.

4.2.4.

Association

An ASSOCIATION defines a semantic relationship (physical or conceptual) between CLASSES. In other words, an ASSOCIATION describes a set of relationships that exist between OBJECTS that are instances of the related CLASSES and thus themselves semantically related. The instances of an ASSOCIATION (the LINKS, cf. Section 4.2.8.) are tuples relating instances of the CLASSES. Each tuple value may appear at most once (cf. 2-19). Binary Association A binary ASSOCIATION is an ASSOCIATION among exactly two CLASSES (including the possibility of an ASSOCIATION from a CLASS to itself) (cf. 3-68). Notation A binary ASSOCIATION is drawn as a solid path connecting two CLASS symbols. Both ends may be connected to the same CLASS, but the two ends are distinct (cf. 3-68). In such a case, the LINKS may connect two different instances from the same CLASS or one instance to itself. The latter case may be forbidden by a CONSTRAINT, if necessary (cf. 3-68). "The path may also have graphical adornments attached to the main part of the path itself. These adornments indicate PROPERTIES of the entire ASSOCIATION" (3-68).

Association Name The ASSOCIATION name designates the (optional) name of the ASSOCIATION (cf. 3-68). "It is shown as a name string near the path (but not near enough to an end to be confused with a rolename, cf. also Section 4.2.5.). The name string may have an optional small black solid triangle in it. The point of the triangle indicates the direction in which to read the name. The name-direction arrow has no semantic significance, it is purely descriptive" (3-69). A STEREOTYPE keyword within guillemets may be placed above or in front of the ASSOCIATION name. A PROPERTY string may be placed after or below it (cf. 3-69). Examples The first example in Figure 16 shows a Member-of ASSOCIATION between the CLASSES Person and Committee. That is, instances of Person have a semantic relation to the instances of Committee, that is, are members of the committee instances. The second example shows

102

Basic concepts of the UER

an ASSOCIATION with both ends being connected to the same CLASS. Instances have a worker-boss relationship (note that no explicit name for the ASSOCIATION is given, so we refer to the ASSOCIATION deploying the attached rolenames). Since there is no CONSTRAINT, it is, according to the modeling, in principle possible that a person has a worker-boss relation to him-/herself. The MULTIPLICITY expressions * and 0 . . 1 (cf. Section 4.2.6.) given for the ASSOCIATION indicate that a boss can have the semantic relationship to an unlimited number of workers, whereas a worker can only be in the modeled semantic relation with none or one boss. Person

Member-oi ^· '

worker

Committee

*

boss 0..1

Figure 16. Binary ASSOCIATION (cf. also 3-28)

N-ary Association An n-ary ASSOCIATION is an ASSOCIATION among three or more CLASSES. "Each instance of the ASSOCIATION is an n-tuple of values" (3-79).m Notation "An n-ary ASSOCIATION is shown as a large diamond (that is, large compared to a terminator on a path)107 with a path from the diamond to each [related] CLASS. The name of the ASSOCIATION (if any) is shown near the diamond. Role adornments may appear on each path as with a binary ASSOCIATION. MULTIPLICITY may be indicated; however, QUALIFIERS and AGGREGATION are not permitted" (3-79, cf. also Sections 4.2.5., 4.2.6., 4.2.7., and 5.1.). Example Figure 17 shows an n-ary ASSOCIATION between the three CLASSES Teacher, Class, and Student. The MULTIPLICITY states that one teacher (i.e., instance of Teacher) is related to one class (i.e., instance of Class) and at least two students (i.e., instances of Student), or, that one class has one teacher and at least two students (note that there is no upper limit on the student number), or, that students are related to one class and one teacher, but that there have to be at least two students in the ASSOCIATION.

Static structure concepts

103

Class 1

Student

h-;

< >

H Teacher

Figure 17. N-ary ASSOCIATION

Xor-Association "An xor-CONSTRAINT108 indicates a situation in which only one of several potential ASSOCIATIONS may be instantiated at one time for any single instance. This is shown as a dashed line connecting two or more ASSOCIATIONS, all of which must have a CLASS in common, with the CONSTRAINT string '{xor}' labeling the dashed line" (3-69-3-70). Any instance of the CLASS that has all of the CONSTRAINT ASSOCIATIONS may only participate in one of the ASSOCIATIONS at one time (cf. 3-70). Each rolename (cf. Section 4.2.5.) must be different. (This is simply a predefined use of the CONSTRAINT notation.) Relevance

4.2.5.

General semantic relationships (cf. also Section 6.7.).

Association end

An ASSOCIATION end is simply an endpoint of an ASSOCIATION where it connects to a CLASS. It is part of the ASSOCIATION, not part of the CLASS (cf. 3-71). Each ASSOCIATION has two or more (n for n-ary ASSOCIATIONS) ends, and each ASSOCIATION end is part of one ASSOCIATION. "Most of the interesting details about an ASSOCIATION are attached to its ends. An ASSOCIATION end is not a separable element, it is just a mechanical part of an ASSOCIATION" (3-71). Notation The path may have graphical adornments at each end where the path connects to the CLASS symbol. These adornments indicate PROPERTIES of the ASSOCIATION related to the CLASS (cf. 3-71). The adornments are part of the ASSOCIATION symbol, not part of the CLASS symbol. "The end adornments are either attached to the end of the line, or near the end of the line, and must drag with it" (3-71). The following kinds of adornments may be attached to an ASSOCIATION end (cf. 3-71-3-72):I09

104

Basic concepts of the UER

Multiplicity MULTIPLICITY is specified by a text syntax, cf. Section 4.2.6. It may be suppressed on a particular ASSOCIATION or for an entire diagram. Qualifier A QUALIFIER is optional, but not suppressible. See Section 4.2.7. Navigability An arrow may be attached to the target end of the path to indicate that navigation is supported toward the CLASS symbol attached to the arrow. This specifies whether traversal from a source instance to its associated target instances is possible. Arrows may be attached to zero, one, or two ends of the path. To be totally explicit, arrows may be shown whenever navigation is supported in a given direction. Rolename A rolename is a name string near the end of the path. "It indicates the role played by the CLASS attached to the end of the path near the rolename" (3-72). In other words, it specifies the function which the instances of the CLASS, i.e. the OBJECTS, have in the described semantic relationship. The rolename is optional. Aggregation Indicator In a binary ASSOCIATION, a hollow diamond is attached to the end of the path to indicate AGGREGATION (cf. Section 5.1.). The diamond may not be attached to both ends of a line (cf. 772). It is attached to the CLASS that is the determiner. Semantic features which are propagated or controlled by the determiner are depicted as PROPERTIES attached to the AGGREGATION indicator. N-ary ASSOCIATIONS may not contain the AGGREGATION marker on any end.

Examples The first example in Figure 18 shows an AGGREGATION relation which is further specified as meronomic relationship by the corresponding STEREOTYPE. The AGGREGATION indicator is attached to the CLASS Car, which accordingly is the determiner. Because we are dealing with a meronomy, this entails that Chassis is a part of Car, and because of the MULTIPLICITY given, each chassis (i.e., instance of Chassis) is part of one car and each car comprises exactly one chassis. The second example displays two ASSOCIATIONS between Bank and Person. In one relation a person (instance of Person) works for the bank (as the name of the ASSOCIATION indicates) and is thus given the Employee role. In the other relation a person has the Customer role. This ASSOCIATION comprises a QUALIFIER that is attached

Static structure concepts

105

to the Bank CLASS and partitions the relationship with regard to account numbers. Due to this partition, there is no or one customer per account number in the relationship, as the MULTIPLICITY indicates.

Car

works lor

K>

·™™°"Ύ·

1 Cha»«l»

tmpnoyee

Person /

^ Bank

0..1 | Custom

Figure 18. Various adornments on ASSOCIATION ends

4.2.6. Multiplicity "A MULTIPLICITY item specifies the range of allowable cardinalities that a set may assume" (3-75). MULTIPLICITY specifications may be given for roles within ASSOCIATIONS,110 ATTRIBUTE values, and other purposes. Essentially, a MULTIPLICITY specification is a subset of the open set of nonnegative integers (cf. 3-75).in Notation "A MULTIPLICITY specification is shown as a text string comprising a comma-separated sequence of integer intervals, where an interval represents a range of integers, in the format: lower-bound'..' upper-bound where lower-bound and upper-bound are literal integer values, specifying the closed (inclusive) range of integers from the lower bound to the upper bound. In addition, the star character (*) may be used for the upper bound, denoting an unlimited upper bound [i.e., any cardinality may be assumed by a set]. ... If a single integer value is specified, then the integer range contains the single integer value. If the MULTIPLICITY specification comprises a single star (*), then it denotes the unlimited nonnegative integer range, that is, it is equivalent to 0..* (zero or more). A MULTIPLICITY of 0..0 is meaningless as it would indicate that no instances can occur" (3-75).

106

Basic concepts of the UER

Examples

Some examples of MULTIPLICITY notation are:

0..1 1

1..6 * 1..3,7..10,15,19..* 4.2.7. Qualifier A QUALIFIER is an ATTRIBUTE or list of ATTRIBUTES whose values serve to partition the set of instances that are associated with an instance at the qualified end (where the qualified end is the end to which the QUALIFIER is attached) (cf. 2-67, 3-76). The QUALIFIER is attached to the source end of the ASSOCIATION. An instance of the source CLASS, together with a value of the QUALIFIER, uniquely select a partition in the set of the target CLASS instances on the other end of the ASSOCIATION (i.e., every target falls into exactly one partition) (cf. 3-76). In other words, a QUALIFIER declares a partition of the set of instances of the CLASS on the other end of the ASSOCIATION. "QUALIFIERS are ATTRIBUTES of the ASSOCIATION" (3-76). Notation A QUALIFIER is shown at the source end of the ASSOCIATION as a small solid-outline rectangle attached to the end of the path between the final path segment and the CLASS symbol that it connects to (cf. 3-76). The QUALIFIER rectangle is part of the ASSOCIATION path, not part of the CLASS. "The MULTIPLICITY attached to the target end denotes the possible cardinalities of the set of target instances selected by the pairing of a source instance and a QUALIFIER value. Common values include: - "0..1" (a unique value may be selected, but every possible QUALIFIER value does not necessarily select a value). - "1" (every possible QUALIFIER value selects a unique target instance ...). - "*" (the QUALIFIER value is an index that partitions the target instances into subsets).

The QUALIFIER ATTRIBUTES are drawn within the QUALIFIER box. There may be one or more ATTRIBUTES shown one to a line" (3-76). QUALIFIER ATTRIBUTES have the same notation as CLASS ATTRIBUTES, except that valueexpressions are not meaningful and may not be attached. "A QUALIFIER may not be suppressed (it provides essential detail whose omission would modify the inherent character of the relationship)" (3-77).

Static structure concepts

107

Examples For the first of the two examples in Figure 19, cf. the discussion of Figure 18. The second example might be expected to express a general linguistic tendency. The ASSOCIATION is qualified with respect to plural affixes. Due to the QUALIFIER and the MULTIPLICITY expression for the CLASS Stem, for each stem (instance of the CLASS Stem) there is either no or one plural affix. That means that a stem cannot be combined with two different plural affixes.

Customer

Bank

0..1

Figure 19. Qualified ASSOCIATION (cf. also 3-77)

Relevance tionships.

4.2.8.

Refinement, categorization, and partitioning of semantic rela-

Link

"A LINK is a tuple (list) of OBJECT references. Most commonly, it is a pair of OBJECT references" (3-84). It is an instance of an ASSOCIATION, and thus a relation between CLASS instances. Notation "A binary LINK is shown as a path between two instances. In the case of a LINK from an instance to itself, it may involve a loop with a single instance.... A rolename may be shown at each end of the LINK. An ASSOCIATION name may be shown near the path. If present, it is underlined to indicate an instance. LINKS do not have instance names, they take their identity from the instances that they relate. MULTIPLICITY is not shown for LINKS because they are instances" (3-84). Other ASSOCIATION adornments (AGGREGATION, cf. Section 5.1., or navigation and the like) may be shown on the LINK ends. A QUALIFIER may be shown on a LINK (cf. 3-84).

108

Basic concepts of the UER

Example Figure 20 comprises five LINKS between the DGf S as an instance of Society and three different instances of the CLASS Person. One LINK carries an explicit name which is the underlined (and thus instantiated) name of the corresponding ASSOCIATION. The LINK takes its identity from relating the OBJECT Hero with the OBJECT DGf S, with the role of the first OBJECT being specified as member. member

Hero : Person Member-of

officer

(treasurer

Tatlana : Person

member

DGfS : Society [president] officer

Angelika : Person member

Figure 20. LINKS (cf. also 3-85)

N-ary Link "An n-ary LINK is shown as a diamond with a path to each participating instance" (3-85). For the other adornments on the ASSOCIATION and on the ASSOCIATION ends, the same applies as to binary LINKS. Link Object A LINK OBJECT is a special kind of LINK, which at the same time is also an OBJECT. It is an instance of an ASSOCIATION CLASS (cf. Section 4.2.9.). Since an OBJECT may change its CLASSES this is also true for a LINK OBJECT. However, one of the CLASSES must always be an ASSOCIATION CLASS (cf. 2-114). Relevance Particular semantic relations between entities, instances of semantic relations as represented by ASSOCIATIONS.

4.2.9.

Association class

"An ASSOCIATION CLASS is an ASSOCIATION that is also a CLASS" (2-21) and thus has CLASS properties. Or - from a different perspective - it is a

Static structure concepts

109

CLASS that also has ASSOCIATION properties (cf. 3-77). An ASSOCIATION CLASS does not only connect CLASSES, but also defines a set of features that belong to the relationship itself and not to any of the CLASSES (cf. 2-21). An ASSOCIATION CLASS is both an ASSOCIATION, connecting CLASSES, and a CLASS, and as such has features and might be included in other ASSOCIATIONS (cf. 2-67). "The semantics of an ASSOCIATION CLASS is a combination of the semantics of an ordinary ASSOCIATION and of a CLASS" (2-67). It "is really just a single model element" (3-77). As an ASSOCIATION CLASS is in particular a CLASS, all that has been said about CLASSES also applies to ASSOCIATION CLASSES. The same is true for statements about ASSOCIATIONS. Notation "An ASSOCIATION CLASS is shown as a CLASS symbol (rectangle) attached by a dashed line to an ASSOCIATION path. The name in the CLASS symbol and the name string attached to the ASSOCIATION path are redundant and should be the same. The ASSOCIATION path may have the usual adornments on either end" (3-78). Conceptually, the ASSOCIATION CLASS and the ASSOCIATION it is attached to are the same semantic entity; however, they are graphically distinct (cf. 3-69). The dashed line must remain attached to the path and the CLASS symbol. In an n-ary ASSOCIATION "an ASSOCIATION CLASS symbol may be attached to the diamond by a dashed line" (3-79). 01

' Company

Figure 21. ASSOCIATION CLASS (cf. also 3-78)

Example Figure 21 shows the Job ASSOCIATION CLASS displaying a relation between the CLASSES Person and Company. The relation relates instances of the CLASSES via a specification of the work the person does for the company. The name of the ASSOCIATION CLASS is given in the CLASS symbol that is attached to the ASSOCIATION'S path by a dashed line. Additional characteristics of a job, such as salary, job description etc. are modeled as ATTRIBUTES in Job, i.e., as ATTRIBUTES of the relation itself.

110

Basic concepts of the UER

Relevance Semantic relationships with conceptualized characteristics and properties (cf. Section 6.4.).

4.2.10.

Generalization

"A GENERALIZATION is the taxonomic relationship between a more general element (the parent) and a more specific element (the child) that is fully consistent with the first element and that adds additional information" (3-86). GENERALIZATION means that instances of the child may be used anywhere the parent may appear, but not the reverse. In other words, the child is substitutable for the parent (substitution principle, cf. Booch, Rumbaugh, and Jacobson 1999:64). A child inherits the properties of its parents, i.e., it has all of its parents' properties and relationships. An element that has no parent and one or more children is called a root element, an element that has no children is called a leaf. An element that has exactly one parent is said to use single inheritance; an element with more than one parent is said to use multiple inheritance (Booch, Rumbaugh, and Jacobson 1999:64). In the UER, multiple inheritance is allowed: an element may have zero, one, or more parents. GENERALIZATION is used for CLASSES, ASSOCIATIONS, EVENTITY FRAMES, TEMPLATES (cf. Sections 5.4. and 5.5. for the latter two), and other elements. It may only be defined between elements of the same kind and a GENERALIZATION hierarchy must not be cyclic (Oevergaard 1998:11). Notation "GENERALIZATION is shown as a solid-line path from the child (the more specific element, such as a subCLASS) to the parent (the more general element, such as a superCLASS), with a large hollow triangle at the end of the path where it meets the more general element" (3-86). "A group of GENERALIZATION paths for a given parent may be shown as a tree with a shared segment (including the triangle), branching into multiple paths to each child. If a text label is placed on a GENERALIZATION triangle [or segment] shared by several GENERALIZATION paths to children, the label applies to all of the paths. In other words, all of the children share the given PROPERTIES" (3-87). When generalizing ASSOCIATIONS, an ASSOCIATION can be shown as an ASSOCIATION CLASS for the purpose of attaching GENERALIZATION adornments, i.e. each ASSOCIATION is represented as an ASSOCIATION CLASS and the GENERALIZATION arrow is drawn between the rectangles for the ASSO-

Static structure concepts

111

CIATION CLASSES. This approach can be used even if an ASSOCIATION does not have any additional ATTRIBUTES, because a degenerate (i.e., empty) ASSOCIATION CLASS is a legal ASSOCIATION (cf. 3-86). "A GENERALIZATION path may have a text label called a discriminator that is the name of a partition of the children of the parent. The child is declared to be in the given partition. The absence of a discriminator label indicates the 'empty string' discriminator which is a valid value (the 'default' discriminator)" (3-86). The discriminator must be unique among the ATTRIBUTES and ASSOCIATION roles of the given parent. Multiple occurrences of the same discriminator name are permitted and indicate that the children belong to the same partition (cf. 3-87). The existence of additional children in the model that are not shown on a particular diagram may be shown using an ellipsis ("...") (cf. 3-86). "Note that this does not indicate that additional children may be added in the future. It indicates that additional children exist right now, but are not being seen. This is a notational convention that information has been suppressed, not a semantic statement" (3-86). CONSTRAINTS may be used to indicate semantic CONSTRAINTS among the children. A comma-separated list of CONSTRAINTS is placed in braces either near the shared triangle (if several paths share a single triangle) or near a dotted line that crosses all of the GENERALIZATION lines involved (cf. 387). The following predefined CONSTRAINTS (among others, possibly also user-defined) may be used: overlapping, disjoint, complete, and incomplete (cf.3-87).112 Examples Figure 22 shows two examples containing GENERALIZATION relations. The first is an example where the CLASSES WindPoweredVehicle, MotorPoweredVehicle, Water-Vehicle, and LandVehlcle all inherit from the CLASS Vehicle. They are subCLASSES of Vehicle and inherit all of its properties. The GENERALIZATION relations have discriminators that partition the children of Vehicle into those discriminated by the kind of power and those discriminated by the nature of the venue. Moreover, there is a second level of inheritance: Sailboat and Truck inherit from particular children of Vehicle and thus from Vehicle. On this second level multiple inheritance is involved. For instance, Sailboat is a child of both WindPoweredVehicle and WaterVehicle. The second example displays both a shared segment of the GENERALIZATION and the CONSTRAINT {disjoint} that applies, accordingly, to both of the children of Entity.

112

Basic concepts of the U ER

That is, a particular entity can either be an ineventity or an eventity but not both. What is displayed here, is part of the participant ontology to be discussed in Section 6.5.

Entity

liMventlty

Eventity

Figure 22. GENERALIZATION (cf. 3-89)

Relevance Hyponomic relations (inheritance relations); specification of general super- vs. sub-concept relations, specification of ontologies (cf. Section 6.8.).

4.2.11.

Dependency

"A DEPENDENCY indicates a semantic relationship between two model elements (or two sets of model elements). It relates the model elements themselves and does not require a set of instances for its meaning. It indicates a situation in which a change to the target element may require a change to the source element in the DEPENDENCY" (3-90). That is, a DEPENDENCY states that the semantics of one or more elements requires the presence of one or more other elements (cf. 2-73). This implies that if the supplier (cf. below) is somehow modified, the dependents (or clients, cf. below) probably must also

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be modified (cf. 2-73). DEPENDENCY is a term of convenience for a relationship other than ASSOCIATION, GENERALIZATION, AGGREGATION and flow relationship (cf. 2-33). Notation "A DEPENDENCY is shown as a dashed arrow between two model elements. The model element at the tail of the arrow (the client) depends on the model element at the arrowhead (the supplier). The arrow may be labeled with an optional STEREOTYPE and an optional individual name. It is possible to have a set of elements for the client or supplier. In this case, one or more arrows with their tails on the clients are connected to the tails of one or more arrows with their heads on the suppliers. A small dot can be placed on the junction if desired. A NOTE on such a DEPENDENCY should be attached at the junction point" (3-90).113 The kinds of DEPENDENCY listed in Table 5 are predefined and may be indicated with keywords (cf. also Section A.I.)· All of these are shown as dashed arrows with keywords in guillemets (cf. 3-90-3-91). Table 5. Predefined kinds of DEPENDENCY

Keyword

Name

Description

bind

binding

A binding relationship of TEMPLATE parameters to actual values. See Section 5.5. for more details.

derive

derivation

A computable relationship between one element and another (i.e., the client may be computed or inferred from the supplier).

refine

refinement

A relationship that represents a fuller specification of a model element that has already been specified at a certain level of detail. Note that this is purely a notational term and that no semantic changes are involved.114

Example Figure 23 displays a DEPENDENCY relation between the CLASS Human as supplier and the OBJECT Alexander as client. Specifically, the relation is an «instanceOf» relation, i.e., Alexander is an instance of Human. Showing this as DEPENDENCY relation emphasizes that if the specification of the CLASS is changed, this will have effects on the specification of the OBJECT.

Relevance Dependencies between concepts differing from other semantic relationships discussed for the UER.

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Basic concepts of the U ER Human

«mstanceOf»

| Alexander | Figure 23. DEPENDENCY

4.2.12.

Derived element

A DERIVED ELEMENT is one that can be inferred or computed from another one (cf. 3-93), but that is shown for clarity even though it can be completely derived from other elements and therefore adds no semantic information. Notation "A DERIVED ELEMENT is shown by placing a slash ("/") in front of the name of the DERIVED ELEMENT, such as an ATTRIBUTE or a rolename" (3-93).

4.3.

Dynamic structure concepts

In this section some dynamic structure elements of the UER will be introduced (more advanced dynamic structure concepts are described in Chapter 5.). These elements model the behavior and interaction of OBJECTS, i.e. of elements of the instance level. They are constructs used for modeling the dynamic, behavioral aspects of the eventities in question. We will specify model elements deployable to describe sequences of states and actions through which elements proceed. Details concerning implementation are omitted in the following representation, which often leads us to slightly different model elements than the UML provides. Still, the semantics and notation described in this section are to some extent from the specification of the UML's statechart and activity diagrams.'15 The former ones are substantially those of David Harel's startcharts (cf., e.g., Harel 1987) - with modifications to make them object-oriented (cf. 3-136). The more or less rigid distinction that is being made in the UML between statechart and activity diagrams has been given up in the UER due to the UER's primary aim in arriving at a single frame for describing verbal semantics, and because we

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consider the destination made in the UML at present as too vague in many regards. This also results in abandoning some of the notions and distinctions made in the UML's statechart and activity diagrams. The UER's statechart diagrams include both active and passive aspects of dynamicity, such as an abstract or concrete entity's performing of actions as well as its changing of states because of influences from other abstract or concrete entities (cf. also Sections 4.3.2. and 4.3.3.). A statechart diagram in the UER is a graph that represents a STATE machine, that is, a finite state-transition system. STATES and various other types of vertices (PSEUDOSTATES, cf. Section 4.3.6.) in the STATE machine graph are rendered by appropriate STATE and PSEUDOSTATE symbols, while TRANSITIONS (cf. Section 5.2.) are generally rendered by directed arcs that inter-connect the former (cf. 3-137). In order to enable the modeling of inherent structure in conceptualization and semantics, "STATES may also contain subdiagrams by physical containment or tiling" (3-137).

4.3.1.

State

The characteristics, relationships, and (inter-)actions of an OBJECT determine the actual OBJECT state in which the OBJECT is at that particular moment. OBJECT states in which the OBJECT shows qualitatively the same reaction to incoming EVENTS (cf. Section 4.3.8.) with regard to the observed characteristic(s) are considered equivalent and are modeled in a single STATE. Thus, "a STATE is a situation during the life of an OBJECT ... during which it satisfies some condition, performs some action, or waits for some EVENT" (3-138). Therefore, a STATE can be seen to model a situation during which some invariant holds (cf. 2-152). This invariant may represent a passive situation such as an OBJECT being in some state (i.e., satisfying some condition - including the waiting for some external EVENT to occur). However, it can also model active conditions such as the OBJECT'S performance of some action. This distinction of passive vs. active is a reflection of the eventity ontology116 and will be further elaborated on in the Sections 4.3.2., 4.3.3., and 6.9., and it will enter into the discussion in Chapter 8. Concerning the complexity of the internal structure of the STATE, two kinds of STATES are distinguished, namely SIMPLE STATES and COMPOSITE STATES, where the former ones do not have any subSTATES but the latter can be decomposed (cf. 3-138), containing concurrent regions and/or sequential subSTATES (as described in Section 4.3.4.).

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"Conceptually, an OBJECT remains in a STATE for an interval of time. However, the semantics allow[s] for modeling 'flow-through* STATES which are instantaneous as well as TRANSITIONS that are not instantaneous" (3138). Notation Generally, "a STATE is shown as a solid-outline rectangle with rounded corners" (3-139), though in the case of ACTIVE SIMPLE STATES a slightly different graphical symbol is applied (cf. Section 4.3.3.). A SIMPLE STATE may be subdivided into two compartments separated from each other by a solid horizontal line. They are as follows (cf. 3-139): Name Compartment This compartment holds the (optional) name of the STATE. PROPERTIES of the STATE are shown below the name. In general, the name is selected in a way such that it reflects the condition that holds for the OBJECT while it is in the STATE. "STATES without names are anonymous and are all distinct. It is undesirable to show the same named STATE twice in the same diagram [if it applies to the same OBJECT], as confusion may ensue" (3-139). If the STATE is a COMPOSITE STATE (cf. Section 4.3.4.), the name compartment is omitted. Instead, the COMPOSITE STATE may have an attached name tab. The optional "name tab is a [solid-outline] rectangle, usually resting on the outside of the top side" (3-139) of a COMPOSITE STATE. It contains the name of that STATE. Internal Transitions Compartment This compartment holds a list of internal actions that are performed while the OBJECT is in the STATE. The notation for each of these list items has the following general format: action-label '/' action-expression The action label normally "identifies the circumstances under which the action specified by the action expression will be invoked" (3-139); typically the action is triggered by an incoming EVENT (cf. Section 4.3.8.). A number of action labels are reserved in the UML for various special purposes and, therefore, cannot be used as user-defined action labels. The following are the reserved action labels that are possibly of interest to the user of the UER (note that there are further action labels reserved in the UML such as the do-label): —

entry "This label identifies an action, specified by the corresponding action ex-

Dynamic structure concepts

-

-

117

pression, which is performed upon entry to the STATE (entry action)" (3139). exit "This label identifies an action, specified by the corresponding action expression, that is performed upon exit from the STATE (exit action)" (3-139). include "This label is used to identify a SUBMACHINE invocation. The action expression contains the name of the SUBMACHINE that is to be invoked"(3140). SUBMACHINE STATES and the corresponding notation are described in Section 4.3.5.

In all other cases, the action label identifies the EVENT that triggers the corresponding action represented by the action expression. These cases are called internal TRANSITIONS, which are semantically equivalent to self TRANSITIONS (cf. Section 5.2.1.) except that the STATE is not exited or re-entered, and thus the corresponding exit and entry actions are not performed (cf. 3-140). The format for specifying an internal TRANSITION is the general format for specifying TRANSITIONS: event-name '[' guard-condition ']' '/' action-expression If there is a GUARD condition (cf. Section 4.3.9.), it has to be specified; otherwise the square brackets are omitted together with the GUARD condition. "Each EVENT name may appear more than once per STATE if the GUARD conditions are different" (3-140). If there is no triggering EVENT conceptualized, the EVENT name is omitted. If there is a triggering EVENT (and thus a reason conceptualized), but this is not specified, the underscore (' ') is used in the place of the EVENT name (for further usages of the underscore cf. Sections 4.3.3., 4.3.10. and 5.5.3.). The internal TRANSITIONS compartment is suppressed (and also the horizontal line for compartment separation), if its list is empty. An alternative notation - besides the string specification within the internal TRANSITIONS compartment - can also be used. The graphical alternative notation is sensible in cases where actions include the sending of SIGNALS. It is similar to the notation of self TRANSITIONS. The internal TRANSITION is shown as a solid arrow originating from a small hollow, solid-outline rectangle within the STATE'S internal TRANSITIONS compartment and terminating with the arrow head on another small, solidoutline hollow rectangle within the the same compartment. The small hollow, solid-outline rectangles function as graphical 'anchors' for the internal TRANSITION. The TRANSITION arrow might for reasons of notational

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clarity cross the STATE-boundary and thus notationally leave the STATE, although the OBJECT does not leave the STATE. The string specification (the TRANSITION signature) can be attached to the arrow, and a SIGNAL sending symbol (pentagon, cf. Section 4.3.8.) may be shown on the TRANSITION arrow.117

Examples Figure 24 displays an example of a STATE where the name reflects the condition that holds for the OBJECT while it is in the STATE, namely being awake.

Figure 24. STATE

Figure 25 shows the different variants of internal TRANSITIONS notation. Both shown STATES contain exactly the same information. In the first one, all internal TRANSITIONS are specified as strings in the internal TRANSITIONS compartment, whereas the second one comprises the graphical notation of two internal TRANSITIONS. When the TypingPassword STATE is entered, the entry action of setting the echo invisible is carried out. The typing in of a character is an EVENT which triggers the handling of that character, but the STATE is not left. Finally, when the typing is over and the STATE is accordingly left, the exit action of setting the echo back to normal is carried out.

TypingPassword

entry / set echo invisible exit / set echo normal character / handle character help / display help

TypingPassword

entry / set echo invisible exit / set echo normal

help / display help

character / handle character

Figure 25. Internal TRANSITION (cf. also 3-140)

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119

Relevance General situation during which some invariant holds for an entity, categorization of situations according to an entity's reaction and general behavior (cf. Section 6.9.). In the next sections, the following different types of STATES and their notations will be introduced: PASSIVE SIMPLE STATES, ACTIVE SIMPLE STATES, and COMPOSITE STATES with concurrent regions and with sequential SUbSTATES.

4.3.2.

Passive simple state (PSS)

A PASSIVE SIMPLE STATE (PSS) is a SIMPLE STATE in which the modeled OBJECT satisfies some condition (including the waiting for some EVENT to occur, as is further specified in Sections 4.3.8. and 5.2.1.). This entails that the OBJECT is characterized as being passive while in a PSS and thus primarily undergoes influences from other entities. In particular, the OBJECT has neither any deliberate influence on the flow of control nor will it leave the STATE intentionally. What is a possible scenario, though, is that the condition expressed by the STATE ceases to hold (without any reason or cause for this being conceptualized). Then, the OBJECT leaves the STATE without the occurrence of any external EVENT being conceptualized that triggers the outgoing TRANSITION. (Note that any TRANSITION, except for internal TRANSITIONS, causes the exiting of a STATE and the entering of another.) Internal TRANSITIONS are nevertheless allowed in PSSs, apart from invoking complex, that is decomposable, SUBMACHINES (cf. Section 4.3.5.) as we are dealing with SIMPLE STATES.118 Moreover, OBJECTS in a PSS are capable of receiving and sending SIGNALS (and thus in particular of raising EVENTS, cf. Section 4.3.8.). Notation A PSS is shown with the rectangle used for STATES, where the name of the STATE displays the condition that is satisfied by the OBJECT. The other notational features of STATES, such as the internal TRANSITIONS compartment, can be applied as well. In the case of a TRANSITION from the PSS where the triggering EVENT is not conceptualized, the TRANSITION has to be marked by the STEREOTYPE «spontaneous» (cf. Section 5.2.1.) to indicate that the OBJECT leaves the PSS spontaneously. Examples Four different PSS's are displayed in Figure 26, with their respective names indicating the condition that holds.

120

Basic concepts of the U ER Happy

Sad

Healthy

III

Figure 26. PASSIVE SIMPLE STATE

Relevance States or passive behavioral conditions of entities, i.e., entities are characterized as reactive.

4.3.3.

Active simple state (ASS)

An ACTIVE SIMPLE STATE is the counterpart of the PSS within the SIMPLE STATES. An OBJECT that is in an ASS is characterized as active, i.e., it performs some action. Actions as they are understood in the UER framework are not necessarily intentional. In particular, this entails that entities which are not attributed any consciousness may also perform actions and thus be in an ASS. There are two types of ASS that are considered to be relevant: one in which the action is considered non-durative, i.e., though logically an action takes some time, this is not conceptualized, and another where the action is characterized as ongoing. That is, it is part of the conceptualization that the action has a duration, but because of its homogeneity the action is still understood as being a 'simple' one (i.e., it is not conceptually decomposed and thus can be modeled in an ASS in contrast to being modeled in a COMPOSITE STATE). Following Vendler's terminology (cf. Section 2.1.2.2.), the latter ongoing actions will be termed activities, whereas we will refer to the former punctiform actions as acts. Activities are in principle conceptualized as unbounded (and thus atelic) actions where there is no inherent beginning or end. An activity starts upon the OBJECT'S entering the STATE (following the entry action, if there is one). It is completed at the moment the OBJECT leaves the ASS (only followed by the exit action, if there is one). Therefore, an activity ASS is normally left when an EVENT (cf. Section 4.3.8.) occurs which triggers an outgoing TRANSITION, though the possiblity of a spontaneous TRANSITION and hence of an abandoning of the activity ASS is not generally excluded (such a TRANSITION has to be marked by the STEREOTYPE «spontaneous», cf. Section 5.2.1.). The other features of STATES (cf. Section 4.3.1.) - apart from invoking complex SUBMACHINES, cf. the PSSs - such as internal TRANSITIONS, are nevertheless allowed in ASSs (and notated accordingly).

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121

Notation An ASS is shown as a shape with straight top and bottom and with convex arcs on the two sides.119 The expression describing the action is placed as a name in the symbol. If an activity is specified in the ASS, an infinity icon (j

Idle

Dynamic structure concepts

129

Choice Pseudostate A choice vertice, when reached, results in the dynamic evaluation of the GUARDS of its outgoing TRANSITIONS (cf. Sections 4.3.9. and 5.2.). This realizes a dynamic (conditional) branch (cf. 2-152). It allows splitting "an incoming TRANSITION into several disjoint outgoing TRANSITIONS. Each outgoing TRANSITION has a GUARD condition that is evaluated after prior actions on the incoming path have been completed" (2-92). The value of these GUARDS may thus be a function of and dependent on the actions of the incoming transition(s). Cf. also Section 5.2.4. Notation A choice PSEUDOSTATE is represented by a small hollow circle, a choice point. Relevance Transient states of particular importance within the model (initial, history, join, fork, junction, choice PSEUDOSTATES) and conceptually relevant 'non-states' (create, destroy, gradual PSEUDOSTATES).

4.3.7.

Final state

A final STATE is a special kind of STATE signifying that the enclosing region or COMPOSITE STATE is completed. A final STATE cannot have any outgoing TRANSITIONS. Nevertheless, it raises a completion EVENT which may trigger a completion TRANSITION on the enclosing STATE (displayed as an unlabeled TRANSITION). The final STATE is the counterpart of the initial PSEUDOSTATE, but since it is not transient, it is not a PSEUDOSTATE itself. Notation A final STATE is shown as a circle surrounding a small filled circle: (ft. 125 Examples Figure 28 on p. 123 depicts three final STATES, two of which belong to concurrent regions of the embedded COMPOSITE STATE. When both are reached, a completion TRANSITION from the COMPOSITE STATE to Inspect is triggered.

4.3.8.

Event

An EVENT is a noteworthy occurrence, noteworthy in that it is conceptualized as a potential trigger of a TRANSITION in statechart diagrams (cf. also 3-143 and Section 5.2.1.). By default, the occurrence "is assumed to take place at

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Basic concepts of the UER

an instant in time with no duration" (2-150), as long as it is not specified otherwise.126 EVENTS may be of different kinds (not necessarily mutually exclusive): Signal Event The receipt of an explicit SIGNAL (i.e., an asynchronous stimulus communicated among instances) of one OBJECT from another results in a SIGNAL EVENT instance.127 "It is denoted by the signature128 of the EVENT as a trigger on a TRANSITION" (3-144). A SIGNAL signature marked by a preceeding «continuous» keyword is understood as being durative, that is, as long as the SIGNAL sending OBJECT is in the STATE from which the SIGNAL is being sent, this SIGNAL is active continuously and thus the triggered TRANSITION is gradual.129 A SIGNAL can be specified as a subsiGNAL of another SIGNAL, i.e., SIGNALS may appear in a GENERALIZATION hierarchy. "This indicates that an occurrence of the subsiGNAL triggers any TRANSITION that depends on the SIGNAL EVENT or any of its ancestors" (3-144). In the UER there is one important SIGNAL EVENT that is predefined and represents the CAUSE operator. It is accordingly named cause (cf. also Section 6.10. and, among others, Jackendoff 1983; Van Valin and LaPolla 1997). A cause-siGNAL that triggers a gradual TRANSITION and that is not supplemented by «continuous» is an initiator of the TRANSITION, as its existence is not conceived as being coextensive with the TRANSITION. Change Event "A designated condition becoming true (described by a Boolean expression) results in a change EVENT instance. The EVENT occurs whenever the value of the expression changes from false to true. Note that this is different from a GUARD condition. A GUARD condition is evaluated once whenever its EVENT fires. If it is false, then the TRANSITION does not occur and the EVENT is lost" (3-144). Time Event "The passage of a designated period of time after a designated EVENT (often the entry of the current STATE) or the occurrence of a given date/time" (3-144) results in a time EVENT instance. Completion Event The completion of all actions or subSTATES in the current STATE (e.g., of all regions in a COMPOSITE STATE) generates a completion EVENT. "This EVENT is an implicit trigger for a completion TRANSITION" (2-165).

Dynamic structure concepts Notation

131

Different EVENT types are notated differently:

Signal Event A SIGNAL EVENT can be defined using the following format (cf. 3-144): event-name '(' comma-separated-parameter-list ')' where the parameter list is optional (and probably in most cases not specified and omitted together with the brackets). A parameter has the format (cf.3-144): parameter-name ':' type-expression A SIGNAL can be declared using the «signal» keyword on a CLASS symbol (a rectangle, cf. Section 4.2.1.). Such a declaration defines a SIGNAL name that may be used in models to represent triggers of TRANSITIONS. The parameters (if any) are specified as ATTRIBUTES (cf.3-144) in the ATTRIBUTE compartment. The following icons provide explicit symbols for specifying the sending and receipt of SIGNALS. It is important to note "that a SIGNAL EVENT represents the reception of a particular (asynchronous) SIGNAL. A SIGNAL EVENT instance should not be confused with the action, such as send action, that generated it" (2-152). Signal Sending "The sending of a SIGNAL may be shown as a convex pentagon that looks like a rectangle with a triangular point on one side (either side). The signature of the SIGNAL is shown inside the symbol. An unlabeled TRANSITION arrow is drawn from the previous ... STATE to the pentagon and another from the pentagon to the next ... STATE of the OBJECT" (3-166). As in the UER's EVENTITY FRAMES the STATE machines for two OBJECTS will often be depicted and combined via their interactions (i.e., sending and receiving SIGNALS), a third solid arrow is drawn from the point on the pentagon to the corresponding icon for signal receipt (belonging to the other OBJECT'S STATE machine) in order to link these two. Signal Receipt "The receipt of a SIGNAL may be shown as a concave pentagon that looks like a rectangle with a triangular notch in its side (either side). The signature of the SIGNAL is shown inside the symbol. An unlabeled TRANSITION arrow is drawn from the previous ... STATE to the pentagon and another from the pentagon to the next... STATE" (3-166). A third solid arrow is drawn from the corresponding symbol for SIGNAL sending (in the statechart diagram of the OBJECT

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Basic concepts of the UER

sending the SIGNAL) to the one for SIGNAL receipt in order to link these two.

Figure 32. Symbols for SIGNAL sending and receipt

In the statechart diagram, there is no direct representation of the SIGNAL itself, only its sending and receiving is depicted. The latter results in a SIGNAL EVENT instance which in these cases is not explicitly (and thus redundantly) shown on the TRANSITION it triggers. Change Event "A condition becoming true is shown with the keyword when followed by a Boolean expression. This may be regarded as a continuous test for the condition until it is true" (3-144). Time Event An elapsed-time EVENT can be specified with the keyword after followed by an expression that evaluates at modeling time to an amount of time, such as 'after (9 months)'. If no starting point is indicated, then the amount of time since the entry to the current STATE is meant (cf. 3-144). "Other time EVENTS can be specified as conditions, such as 'when (date = Jan. 21, 2002)'" (3-144). Completion Event As a completion EVENT is the implicit trigger for a completion TRANSITION, it is not shown in any way, i.e., if there is neither an EVENT nor the STEREOTYPE «spontaneous» specified on a TRANSITION, this TRANSITION has to be considered a completion TRANSITION (cf. Section 5.2.1.). Signal Sending With Unspecified Sending Time In a STATE machine, SIGNAL sending can either be modeled as entry action, exit action,130 or as an action of an internal or an outgoing TRANSITION (i.e., when the OBJECT is

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133

still in or leaves the STATE). However, in human conceptualization it often seems to be unimportant (and thus not specified) at what point exactly the SIGNAL is being sent. To be able to model this underspecification, a hollow (preferably isosceles) triangle is used, one side (preferably the basis) of which is fused with one of the sides of the source STATE (the STATE from which the SIGNAL is outgoing). The side is rounded in case it is one of the convex arcs of an ASS. This notation is in particular sensible with all STATES which (might) have a duration, i.e., PSS, activities, COMPOSITE STATES (in particular, sequences of actions) and unspecified actions in ASSs. Examples Figure 33 shows an ASS and a PSS, from which SIGNALS with unspecified sending time are emanating (although the SIGNAL sending pentagons are not shown).

Figure 33. SIGNAL sending with unspecified sending time Relevance

Triggers of changes (cf. Section 6.10.).

4.3.9. Guard GUARDS are conditions that have to be met before TRANSITIONS can fire. When a triggering EVENT occurs, the corresponding TRANSITION fires only if the GUARD condition is true. "A GUARD is a boolean expression that is attached to a TRANSITION as a fine-grained control over its firing. The GUARD is evaluated when an EVENT instance is dispatched. ... If the GUARD is true at that time, the TRANSITION is enabled, otherwise, it is disabled" (2-150). Notation A GUARD is notated as a Boolean expression (or commaseparated list of Boolean expressions) within square brackets: '[' (comma-separated)-Boolean-expression-(list) Examples Figure 31 on p. 128 shows two GUARDS: [temperature < 30°C] and [temperature >= 30°C].

']'

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Basic concepts of the U ER

4.3.10. Swimlane SWIMLANES are a tool to join STATE machines belonging to different OBJECTS into one whole, in which the single STATE machines are concurrently passed through by the corresponding OBJECTS. This enables the user to model interactions between OBJECTS. Each prominent OBJECT (for the notion of prominent participant, cf. Section 5.4.) is attributed a SWIMLANE, in which its STATE machine is displayed. Only SIGNALS, i.e., reflexes of interactions, may pass the border between SWIMLANES. Thereby, SWIMLANES are a concept to assign the flow of control to OBJECTS. Notation A statechart diagram comprising subdiagrams for more than one OBJECT (as present in, e.g., EVENTITY FRAMES, cf. Section 5.4.) "may be divided visually into 'SWIMLANES' "(3-163), vertical regions that are separated from each other by vertical solid lines. The relative ordering of the SWIMLANES has no semantic significance. The arrow connecting the SIGNAL sending and SIGNAL receiving pentagons may cross border lines and also SWIMLANES. The name of the OBJECT a SWIMLANE belongs to is displayed in the upper left corner of the SWIMLANE. If the OBJECT is unspecified, the underscore (' ') is used instead.

Asleep

\L \L Awake

Figure 34. SWIMLANE

Example The example in Figure 34 shows a dynamic core (cf. Section 5.4.1.) which is displayed by the dashed rectangle with rounded corners. This dynamic core contains two SWIMLANES, one for each of the OBJECTS χ and y. Each SWIMLANE models the dynamic aspects and hence behavior of the OBJECT it is owned by. For instance, the left SWIMLANE owned by χ (as indicated in the upper left corner of the SWIMLANE) displays that χ performs the

Dynamic structure concepts

135

action Touch which results in the sending of a cause-SlGNAL. This SIGNAL is received by y, as indicated in the right SWIMLANE owned by y. The receipt of the SIGNAL triggers a TRANSITION of y from the PSS Asleep to the PSS Awake. Relevance

Assignment of behavior to entities.

Chapter 5. Advanced concepts of the UER

In this chapter the advanced concepts of the UER will be presented. These are mostly concepts introduced in order to meet the requirements of our linguistic application domain. The first one, the static AGGREGATION, is a semantic relationship which allows for the modeling of semantic 'propagation' or 'control' of features from one participant131 of an eventity to another. The UER's AGGREGATION extends and fundamentally alters the UML's aggregation, though the notation has partly been adopted.132 As a second advanced concept a dynamic one is introduced: TRANSITION. Though TRANSITIONS have been mentioned several times before and the concept of TRANSITION is one of the most fundamental concepts in state-transition systems, TRANSITIONS are presented in this chapter because of their complexity. The third concept, the dynamic BLACK BOX, enables the modeling of 'possibility' and therefore non-determinism. The fourth, fifth, and sixth - EVENTITY FRAME, TEMPLATE, and SUBCORE STATE - cannot be categorized as either dynamic or static, since they comprise both aspects. The EVENTITY FRAME concept is considered to be the central one in the UER: generally, a verb's reading or an eventity conceptualization is represented using an EVENTITY FRAME. TEMPLATES as such are part of the UML, though the UML focusses on CLASS TEMPLATES. However, in the UER, TEMPLATES will be TEMPLATES of EVENTITY FRAMES in most cases. With EVENTITY FRAME TEMPLATES, systematic relations in the lexicon of a language or between languages can be modeled, if these rely on variable elements being bound to different values to yield different conceptualizations. SUBCORE STATES are a mechanism to reference subeventities of an eventity in the representation. They are a structuring device allowing conceptual clustering within an eventity.

5.1.

Aggregation

AGGREGATION is a special kind of ASSOCIATION relationship. Only binary ASSOCIATIONS may be AGGREGATIONS. AGGREGATION defines a semantic relation, wherein one of the related elements (the determiner) propagates at least one (typically dynamic) semantic feature to the other (the tolerator). Or,

Aggregation

137

the determiner controls at least one semantic feature of the tolerator, where 'control' is understood as an exterior determination of the tolerator's feature. It is necessary for the determiner and the tolerator OBJECTS to have overlapping 'conceptual lifetimes'. That is, at the time of propagation or control both must conceptually exist. Overlapping lifetimes at instance-level is thus an essential (so-called primary) characteristic of AGGREGATION. 133 Another primary characteristic is irreflexivity at the instance-level.134 As an OBJECT cannot propagate or control (in the above sense) a feature of its own, instances of the AGGREGATION relationship are thus irreflexive. At the type-level, it is nevertheless possible to aggregate a CLASS to itself. In this case, every instantiation of the AGGREGATION 135 has to relate two different OBJECTS, both instances of the same CLASS, in order to fulfill the irreflexivity condition at the instance-level. Moreover, the primary characteristic asymmetry holds at the instance-level (but is not a primary characteristic at the type-level), as one related OBJECT functions as the determiner in an AGGREGATION, and the other one as the tolerator. It is possible, though, to have more than one AGGREGATION relationship between two OBJECTS. In such a case, an OBJECT may function as a determiner in one AGGREGATION and as a tolerator in another. In such a case it is essential that the AGGREGATION relationships differ from one another in order to fulfill the asymmetry requirement. Transitivity holds for propagated features. For example, if CLASS A propagates its movements to CLASS B, and CLASS B propagates its movements to CLASS C (note that the same feature has to be propagated in order for transitivity to hold), then A propagates its movements to C as well. That is, if instances of A move from a location l\ to a location /2, instances of C also move from l\ to /2. It becomes obvious in this example that typically some preconditions for semantic propagation must be fulfilled. A precondition that always has to be fulfilled is that the related elements (determiner and tolerator) must (i) both have the corresponding feature or (ii) be able to perform or respectively undergo the corresponding feature (where feature is understood in a broad sense, including actions or changes of states, for instance). In the above example of movement propagation (not movement control), A, B, and C additionally have to be at the same location, l\. It depends on the propagated feature which preconditions are necessary. Transitivity does, of course, not hold for controlled features, even if all affected CLASSES share the feature(s) in question (though a sharing of features is not required for control

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at all, because, e.g., one OBJECT can control another OBJECT'S movements without being able to move itself). AGGREGATIONS may have rolenames and MULTIPLICITY specifications on both ASSOCIATION ends. For example, if the MULTIPLICITY of the determiner end is 0..1, the determiner may have a tolerator but need not. This includes that an existing tolerator may be attached or removed during the modeled time frame and is thus separable from the determiner. Notation AGGREGATION is shown as a binary ASSOCIATION, with a hollow diamond, the AGGREGATION indicator icon (cf. also Section 4.2.5.), attached to the end of the ASSOCIATION path. The diamond may not be attached to both ends of the path. It is attached to the end of the path where it meets the determiner symbol. If there are two or more AGGREGATIONS to the same determiner, they may be drawn as a tree by merging the AGGREGATION end into a single segment. This requires that all of the adornments on the AGGREGATION ends (including PROPERTIES) be consistent. This is purely a presentation option, there are no additional semantics to it. The semantic features which are propagated or controlled by the determiner are depicted as PROPERTIES attached to the ASSOCIATION end with the hollow diamond. For propagation, the PROPERTY propagation, for controlled features, the PROPERTY control is used. The propagation PROPERTY is of the ENUMERATION Propagation which lists all the semantic features that might be propagated, control is of the ENUMERATION Control, whose ENUMERATION literals identify the semantic features that are possibly controlled.136 Both PROPERTIES may take several values at a time which are shown as a list. Therefore, to keep the upper bound open for the time being, the PROPERTY definitions are assigned the MULTIPLICITY '*'. If the MULTIPLICITY at the determiner end is 0..1, the initial state of the AGGREGATION may be specified (i.e., whether tolerator and determiner are aggregated at the beginning of the modeled time slot, i.e. eventity, or not): the PROPERTY islnitial may follow the MULTiPLiciTY-string, where the value false marks that no aggregation is extant at the beginning, whereas the value true marks an AGGREGATION relationship existing at the beginning. In the latter case, the MULTIPLICITY string of the determiner end (including the islnitial PROPERTY) may thus be specified as follows: 0..1 {initial} Example Assume an AGGREGATION that specifies a determiner A to control the color and height of the tolerator B and to propagate its movements

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to B. This is shown in the following PROPERTY string that is attached to the ASSOCIATION end with the hollow diamond:137 (control = (color,height), propagation = movement} Figure 35 shows a corresponding AGGREGATION. A is the determiner, B the tolerator, and the PROPERTY string is given as indicated above. Moreover, the AGGREGATION relationship holds initially, as indicated by the additional PROPERTY initial. But it may terminate during the modeled time frame, as specified by the MULTIPLICITY 0 . . 1. 0..1 {initial}

JO

{control = (color, height), propagation = movement}

Figure 35. AGGREGATION

Relevance Particular semantic relationship: general control or propagation of behavioral features of one entity over or to another (cf. Section 6.7.). In the following sections different subtypes of AGGREGATION relations are introduced, namely MERONOMY, ATTACHMENT, and POSSESSION. Prototypically, MERONOMY is a physical part-whole relationship in which the tolerator is a proper part of the determiner. Thus, the aggregate (as the sum of determiner and tolerator) corresponds to the determiner which physically includes the tolerator. In an ATTACHMENT relationship, the aggregate is the conceptualized unity of determiner and tolerator. Prototypically, there is a physical contact established between the tolerator and the determiner (at the least, the tolerator has to be in the direct surroundings of the determiner). This condition is not necessary in a prototypical POSSESSION, in which the aggregate is not a conceptual unit. The determiner controls all non-intrinsic features of the tolerator, but does not have to be physically close. The spatial relation between determiner and tolerator seems to be the prominent factor for distinguishing the prototypical cases of the AGGREGATION subtypes. In the following specifications of the three subtypes, we will generalize away from physical proximity in order to be able to cover relationships between abstract entities as well. Accordingly, primary characteristics are worked out for each subtype. Moreover, optional (so-called secondary) characteristics are also presented for MERONOMY and ATTACHMENT. These are characteristics

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that might be crucial to the conceptualization of the corresponding AGGREGATION relationship. If they are crucial, they are represented in the model via PROPERTIES, otherwise nothing can be said about their status. Subtypes of the AGGREGATION relationship are notated by the according STEREOTYPES, which are attached to the ASSOCIATION path of the AGGREGATION. These are «meronomy» for MERONOMY, «attachment» for ATTACHMENT, and «possession» for POSSESSION (cf. the following sections).

5.1.1.

Meronomy

MERONOMY is a kind of AGGREGATION which specifies a relation between a whole (the determiner) and a part (the tolerator). A whole has more than one part at the instance level.138 The whole incorporates its parts so that it conceptually corresponds to the aggregate, which is in general understood as the entirety of determiner and tolerator. That is, in such part-whole relationships the aggregate is necessarily conceptualized as a unity (which is not required for general AGGREGATIONS). A whole has an independent ontological existence which transcends its parts, i.e., in this regard its parts are not relevant (cf. Henderson-Sellers and Barbier 1999a: 552). Besides, there are more necessary and thus primary characteristics, which are adopted from Henderson-Sellers and Barbier (1999a, 1999b). These are emergent property (there is a property of the whole that is not evident in the parts, e.g., the functionality of a car is not evident in the car's parts), resultant property (there is a property of the whole which can be deduced from the parts, i.e., the weight of a car can be deduced from the weights of its respective parts), and antisymmetry at the type level (if CLASS A is part of CLASS B, and B part of A, than A and B are identical). As we are looking for a concise treatment of the cognitive phenomena of meronomical systems, the MERONOMY concept introduced here includes different 'flavors' of meronomy. For example, the wheels, the chassis, and the engine are all parts of a car, and a slice is a part of a cake. These examples mirror some of these differences, (i) A car without wheels is still a car, but a car without a chassis is not. (ii) An engine is not visible (and accessible) from the outside, but the wheels are. (iii) Whereas the relation between a car and its wheels or chassis is functional, the one between a cake and one slice of it is not. And, (iv) a slice of a cake and the cake are homeomerous (i.e., similar to each other), but wheels and a car are not. In order to handle these different

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kinds efficiently, secondary characteristics are introduced. These are optional characteristics that might apply to MERONOMY relations. If they apply, they are represented in the model via PROPERTIES. Thereby, it is possible to model the specificities of the particular MERONOMY relations. In Table 6, the secondary characteristics (with the corresponding PROPERTY name and type in italics) are listed, together with a description and an example (cf. Cruse 1986; Henderson-Sellers and Barbier 1999a, 1999b; Saksena et al. 1998; Winston, Chaffin, and Herrmann 1987 for most of the secondary characteristics). Table 6. Secondary characteristics of MERONOMY Secondary characteristic

Description

Example

configurational isConfigurational (Boolean)

A structural and/or functional relationship exists between the different parts of the same whole. (It may be specified using CONSTRAINTS or COMMENTS.)

Different parts of a car, such as engine and tank, are in a structural and functional relationship, whereas different slices of a cake are not.

encapsulated isEncapsulated (Boolean)

The part is internal and not visible or directly accessible from the outside.

An engine is an encapsulated part of a car, whereas the tow-bar is not.

exchangeable isExchangeable (Boolean)

The part can be exchanged for an equivalent one without destroying the integrity of the whole.

Tyres are exchangeable parts of a car, whereas the brain of a person is not.

functional isFunctional (Boolean)

A functional relationship exists between the part and the whole. (It may be specified using CONSTRAINTS ΟΓ COMMENTS.)

A car and its engine block have a functional relationship, whereas a cake and one of its slices do not.

homeomerous isHomeomerous (Boolean)

The part is similar to the whole, i.e., the part and the whole have properties in common.

A slice of a cake and the cake are homeomerous, whereas a university building and the university are not.

homogeneous isHomogeneous (Boolean)

The part is comparable to the other part(s) of the whole in a regarded aspect. The parts are thus conceptualized as congeneric and uniform.

The wheels of a car are homogeneous parts of the car, whereas the brain of a person is not homogeneous to any other part of the person.

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Secondary characteristic mandatory

Description

Example

The part cannot be removed

isMandatory (Boolean)

from the whole without destroying the whole, i.e., it is

A mandatory part of a car is its chassis, whereas seat covers are not.

canonically necessary isNecessary (Boolean)

removable isRemovable (Boolean)

segmental isSegmental (Boolean)

not optional. The part is required with regard to the completeness of the whole (i.e., it is not facultative), but neither is the whole destroyed if the part is removed (it is only defective) nor is the part necessarily not removable. The part can be removed from the whole.

separable isSeparable (Boolean)

The part is the result of a partition (in a non-mathematical sense) and has a spatial cohesiveness (physical or conceptual). The part can be removed from the whole and may exist independently of the whole.

shareable isShareable

The part may belong to two or more wholes at the same

(Boolean)

time.

The rear-view mirror is a canonically necessary part of a car, whereas the chassis as a mandatory part and seat covers as facultative parts are not.

A removable part of a car is the rear-view mirror, whereas sugar is a non-removable part of lemonade. A wheel is a segmental part of a car, whereas sugar is a non-segmental part of lemonade. A sheet of paper is a separable part of a writing pad, whereas a finger of a person is not. A person can be a part of several social groups at the same time, whereas a chassis cannot be a part of several cars at the same time.

We have refrained from establishing a list of orthogonal secondary characteristics on purpose. The characteristics are selected according to their assumed proximity to conceptualization. This implies that the characteristics are not necessarily independent from one another, e.g., 'separable' requires 'removable'. It might be the case that other characteristics will prove sensible as well or better suited for the application domain. Accordingly, they will have to be added to the list or to replace existing secondary characteristics.

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All characteristics are of the type Boolean, i.e., the corresponding secondary characteristic can be specified as holding or not holding. If it is not specified at all, nothing can be said about whether such a characteristic can be established or not. If 'shareable' holds, three types of possible sharings can be identified (depictable as sharing PROPERTY, where Sharing is of the type ENUMERATION with the three ENUMERATION literals: homogeneous, heterogeneous and conceptual), cf. Saksena (1998:276-277): - Homogeneous Sharing: An instance of the part CLASS can be shared among different instances of the same whole CLASS. For example, an instance of Person can belong to two different instances of ResearchGroup. - Heterogeneous Sharing: An instance of the part CLASS can be shared by wholes that are instances of different CLASSES. An instance of Person can be simultaneously shared by an instance of Family and by an instance of ResearchGroup. - Conceptual Sharing: The concept represented by a CLASS is shared. Conceptual sharing does not imply sharing of instances. For example, Engine can be a part of the two different whole CLASSES Car and Plane. However, one particular instance of Engine that is part of an instance of Plane cannot be used as a part of an instance of Car. The concept of Engine is being shared, not instances of Engine.

In most cases transitivity of instances of MERONOMY can be attested to meronomic relationships that have the same secondary characteristics and where the focus lies on the propagation or control of the same semantic features.139 If transitivity is present between two relationships at the instance level in the model, it may thus (but need not) be specified as a CONSTRAINT on both relationships. Notation A MERONOMY is indicated by the STEREOTYPE «meronomy», which is attached to the AGGREGATION path. The secondary characteristics are added as PROPERTIES at the AGGREGATION end with the hollow diamond, integrated into a comma-delimited sequence. They are listed together with the PROPERTIES for propagated or controlled semantic features present in the model. Note that particular secondary characteristics of an entity imply the propagation or control of particular features from the whole to the part. For example, if a car is moved, so are its parts chassis and wheels. Nevertheless, for the sake of conceptual highlighting, it is recommended to include those propagated or controlled features that are important for the concepualization via the PROPERTIES propagation and control in the diagram.

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Example The meronomy or part-whole relation between a car and its chassis is specified as depicted in Figure 36. The STEREOTYPE «meronomy» is attached to the AGGREGATION. Six secondary characteristics are explicitly listed. The part is configurational (it has a structural and functional relationship to other parts), mandatory (if the chassis was removed, the car would be destroyed), and segmental (it constitutes a segment and has a spatial cohesiveness). On the other hand, it is not encapsulated (the chassis is accessible from the outside), not exchangeable (a different car would be conceptualized if the chassis were exchanged), and not shareable (a chassis can only be part of one car). Apart from the importance of those characteristics within the model, movement propagation is furthermore highlighted and depicted as essential.

Car

, «meronomy» < >- -

Chassis

{propagation = movement, configurational, isEncapsulated = false, isExchangeable = false, mandatory, segmental, isShareable = false}

Figure 36. MERONOMY Relevance

Different flavors of part-whole relationships.

5.1.2. Attachment ATTACHMENT specifies an AGGREGATION between a stock (the determiner) and an attached entity (the tolerator). 14° ATTACHMENTS are similar to MERONOMIES in that the aggregate is conceptualized as a unity, i.e., stock and attached entity belong together. However, there is a basic conceptual difference between ATTACHMENT and MERONOMY: no emergent or resultant property has to be assignable to the stock. ATTACHMENTS further differ from MERONOMIES in that the stock does not conceptually include the attached entity, but the latter is appended or linked to the stock. The stock is conceived as more prominent in some respect (such as size or function), prototypically it is "some larger entity" (Cruse 1986: 167), i.e. prominent with respect to physical size. Antisymmetry at the type level does not hold, but similar prominence does. This is one of the primary characteristics of ATTACHMENTS, meaning

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that if A is attached to B, and B is attached to A, then A and B are conceptualized as being equally prominent. Attached entitities are essentially removable from the aggregate (which is thus destroyed), without the stock or the attached entity being affected. In terms of the secondary characteristics defined for MERONOMY (cf. Section 5.1.1.), removable and separable hold between the stock and the attached entity, whereas the attached entity is not canonically necessary for the stock and is also not mandatory, that is, obligatory for the stock to exist. Thus, detachability andfacultativity are primary characteristics of ATTACHMENTS. As secondary characteristics we propose encapsulated, functional, and shareable — in the way they have been defined in Section 5.1.1., but related to stock and attached entity instead of whole and part. Transitivity does not hold for the ATTACHMENT relationship. Notation An ATTACHMENT is indicated by the STEREOTYPE «attachment» which is attached to the AGGREGATION path. The secondary characteristics are added as PROPERTIES at the AGGREGATION end with the hollow diamond, integrated into a comma-delimited sequence. They are listed together with the PROPERTIES for propagated or controlled semantic features present in the model. Cf. also Section 5.1.1. Example Figure 37 depicts the attachment relation between an earring and the person that wears it. The AGGREGATION relation is specified as ATTACHMENT by the «attachment» STEREOTYPE. Via secondary characteristics, it is specified that the earring is not encapsulated (but visible from the outside), not shareable (two different persons cannot wear the same earring at the same time), and that movement from the person to the earring is propagated (naturally, if the person moves, so does the earring). «attachment»

Person

{propagation = movement, isEncapsulated = false, isShareable = false}

Figure 37. ATTACHMENT Relevance Attachment relations.

Earring

146

5.1.3.

Advanced concepts of the U ER

Possession

POSSESSION specifies an AGGREGATION between a possessor (the determiner) and Ά possessee (the tolerator). Differing from MERONOMIES and ATTACHMENTS, the POSSESSION aggregate is not conceptualized as a unity. In particular, possessor and possessee do not belong together, but the possessee belongs to the possessor and is at the possessor's disposal. The possessor as the dominant entity rules and controls the possessee with regard to all its non-intrinsic features. In other words, the possessee cannot influence any of its features while being possessed by the possessor. The possessor may dispose of the possessee (cf. Helbig 2001:73-75). As with ATTACHMENTS, but unlike MERONOMIES, the possessor does not conceptually include the possessee. No emergent or resultant property can be assigned to the possessor. Possessees are essentially removable from the aggregate (which is thus destroyed). The existence of neither the possessor nor the possessee is affected, though. POSSESSIONS therefore include detachability, but one which cannot be initiated or influenced by the possessee itself. Either the possessor disposes of it voluntarily, or the possessee may be taken from the possessor for some reason (typically by a third party). Hence, this kind of detachability is termed unilateral detachability. Another primary characteristic is non-shareability, as the possessor is the only entity to rule over and control the possessee.141 Accordingly, transitivity does not hold between two or more POSSESSION relations, but holds for the implied control of all semantic features. That is, if A possesses B and B possesses C, A can control all semantic features of C via B without itself possessing C. Finally note that the possessee is neither canonically necessary nor mandatory for the possessor, th\is,facultativity also holds as a primary characteristic. No secondary characteristics are specified for POSSESSION in the current state of development of the UER. Notation A POSSESSION is indicated by the STEREOTYPE «possession» which is attached to the AGGREGATION path. PROPERTIES for propagated or controlled semantic features are added at the AGGREGATION end with the hollow diamond, possibly integrated into a comma-delimited sequence. Example Figure 38 shows the possession relation between a person and a car, where the car is the possessee. The relation is indicated by the STEREO-

Transition

147

TYPE «possession» and as conceptually highlighted control feature movement is listed.

«possession»

Car

{control = movement} Figure 38. POSSESSION

Relevance Possession relations (understood in a broad sense as the possessor's control of all non-intrinsic features of the possessee).

5.2.

Transition

In this section, the TRANSITION concept will be presented, starting with simple TRANSITIONS between two STATES (including gradual, self, completion, and spontaneous TRANSITION) and followed by complex TRANSITIONS, TRANSITIONS to and from COMPOSITE STATES, and, finally, factored TRANSITION paths.

5.2.1.

Simple transition

A simple TRANSITION is a relationship between two STATES (cf. 3-146) indicating that, when a specified EVENT occurs, an OBJECT in the first STATE (the source STATE) will leave the first and enter the second STATE (the target STATE) and perform specific actions (if specified), provided that certain conditions are satisfied (if such have been specified as well). "On such a change of state, the TRANSITION is said to 'fire'" (3-146). "The trigger for a TRANSITION is the occurrence of the EVENT labeling the TRANSITION" (3-146). Only in the case of a spontaneous TRANSITION no EVENT and thus no trigger is specified (completion TRANSITIONS are triggered by an implicit completion EVENT, cf. below). If an EVENT can trigger more than one TRANSITION within the same region (that is, not in different concurrent regions), only one will fire. If these conflicting TRANSITIONS are of the same priority,142 an arbitrary one is selected and triggered (cf. 3-146).

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Advanced concepts of the UER

Notation A TRANSITION is shown as a solid arrow originating from the source STATE and terminating with the arrow head on the target STATE. It may be labeled by a TRANSITION string that has the following general format (cf. 3-146): event-signature '[' guard-condition ']' V action-expression If there is no EVENT specified, the TRANSITION is a completion or spontaneous TRANSITION (cf. below). In the case there is no GUARD condition, the square brackets are also omitted, and if there is no action expression, the slash is omitted. STEREOTYPES are placed near the TRANSITION arrow (preferably either above or in front of the TRANSITION string or on the other side of the arrow). The event-signature describes an EVENT with its arguments (cf. 3-146): event-name '(' comma-separated-parameter-list ')' "The guard-condition is a Boolean expression written in terms of parameters of the triggering EVENT and ATTRIBUTES and LINKS of the OBJECT" (3-146) whose state-transition system is modeled by the corresponding SWIMLANE. "The GUARD condition may also involve tests of concurrent STATES 143 of the current machine, or explicitly designated STATES of some reachable OBJECT" (3-146), where "reachable OBJECT" means that the STATES of this OBJECT must be querable within the model. In the latter case the OBJECTname is cited, followed by an access arrow (->) and the STATE-name(s) to describe the designated STATE. Separated by double colons, pathnames of the form 'OBJECT-«tfme->STATEl::STATE2::STATE3' are thereby yielded: STATE names of nested STATES may be fully qualified by the names of the STATES that contain them. "This may [also] be used in case some STATE name occurs in different COMPOSITE STATE regions of the overall machine" (3146). "The action-expression is executed if and when the TRANSITION fires. ... The action expression may be an action sequence comprising a number of distinct actions" (3-146). If an action expression consists of just one action, it is denoted by a name string that identifies the respective action. Otherwise, if several actions are involved, their names are concatenated using semicolons, i.e. an action expression may be represented as a semicolon-separated list of actions: action-name ι ; action-name-i , ... ; action-namen

Transition

149

Action expressions may include actions that explicitly generate EVENTS, such as sending SIGNALS (cf. 3-146), and also activities. In the case of activities the TRANSITION must be conceptualized as having a duration. This is only possible if the TRANSITION is gradual or incremental, which in these cases has to be marked accordingly (cf. below and Section A.I.)· Otherwise, if the OBJECT performs some activity that results in a spot TRANSITION without duration, the respective activity is modeled in the source STATE. Example Figure 39 shows a simple TRANSITION from the source STATE Final Exam into the target STATE Graduate, which is triggered by the EVENT pass. No GUARD condition or action are specified.

Final Exam

Graduate

Figure 39. Simple TRANSITION

Gradual Transition A TRANSITION which is gradually completed and thus entails duration is called a gradual TRANSITION. All features of general TRANSITIONS apply to gradual TRANSITIONS. In spite of simulating a gradual TRANSITION using a transitional STATE (i.e., a SIMPLE STATE representing the TRANSITION) as would be done within the UML framework, UER gradual TRANSITIONS are depicted by a particular PSEUDOSTATE which notationally factors the gradual TRANSITION into two segments (cf. also Section 5.2.4.). This gradual PSEUDOSTATE is shown as a circle surrounding a small hollow circle: © . There are essentially two reasons for the gradual PSEUDOSTATE: (i) a gradual TRANSITION is not a STATE, but a transition that (from a logical point of view) is considered to consist of many intermediate states which are not separately conceptualized and distinguished as such, and (ii) it is sensible to establish a particular notational element to tag gradual TRANSITIONS because of their conceptual importance (similar to the infinity icon for activities, that

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Advanced concepts of the U ER

is, durative actions). It might be helpful to imagine the gradual PSEUDOSTATE as wandering along the time-line of the gradual TRANSITION, highlighting the intermediate states one after the other. Nevertheless, the graphical position of the gradual PSEUDOSTATE on the gradual TRANSITION arrow, in other words, the lengths of the two segments of the gradual TRANSITION arrow, are not meaningful. Gradual TRANSITIONS that include an observable incremental change of the OBJECT (i.e., the undergoing OBJECT is in effect an incremental theme, cf. Note 17 on p. 354) are supplemented by a corresponding STEREOTYPE «incremental». Gradual TRANSITIONS can be interrupted by SIGNAL EVENTS.144 (The other EVENT types are not sensible in this context, because neither completion, nor time or change EVENTS are EVENTS raised by other OBJECTS, which is essential in the conceptualization of interruptions.) In the case of an interruption, the received SIGNAL EVENT is an additional impact on the course of events. Any EVENT triggering a TRANSITION emanating from the gradual PSEUDOSTATE is interpreted as triggering a different course of events than the originally expected or intended one. Therefore, the gradual TRANSITION is interrupted and 'cut into pieces' with a new target STATE being established. The new target STATE is shown as usual, connected to the source gradual PSEUDOSTATE by a solid arrow. If the original target STATE of the gradual TRANSITION (before the SIGNAL EVENT occurred and interrupted) is still conceptualized - this might be the case with eventities in which something is being prevented - it is shown likewise (possibly unspecified), but with a dashed TRANSITION arrow extending to it from the gradual PSEUDOSTATE and thereby representing the intended TRANSITION. Example Figure 40 depicts a gradual TRANSITION of an entity from being a child to being an adult. The gradual PSEUDOSTATE is used to indicate that the TRANSITION is gradual. Self Transition A TRANSITION from a STATE back to itself is called a self TRANSITION. Note that the OBJECT leaves and re-enters the STATE. A self TRANSITION differs from an internal TRANSITION insofar as the exit action is performed when the OBJECT leaves the STATE and the entry action is performed by the OBJECT'S re-entering into the STATE. All features of general TRANSITIONS apply to self TRANSITIONS.

Transition

151

Figure 40. Gradual TRANSITION Example Figure 41 displays an interrupted gradual TRANSITION. The gradual TRANSITION that would have turned an entity from being young into being old is interrupted by a SIGNAL received from a fountain of youth (information that is only added by the NOTE - the modeling itself merely shows the receipt of a cause-siGNAL). The SIGNAL EVENT triggers a return to the STATE Young and hence essentially a self TRANSITION. However, the intended TRANSITION is still conceptualized and part of the model: the original target STATE Old is still shown.

impact of a fountain of youth

Figure 41. Interrupted gradual TRANSITION

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Advanced concepts of the UER

Completion Transition A completion TRANSITION is an outgoing TRANSITION that does not have an explicit trigger but is triggered by a completion EVENT (cf. 2-165 and Section 4.3.8.). It may have a GUARD and action expression defined. Handling Under specification As the constituting elements of a TRANSITION are the source and target STATES and the triggering EVENT, these three are the necessary ingredients for a minimal specification of a TRANSITION. However, in human conceptualization, and thus eventity semantics, there are many cases in which at least one of these elements is not fully specified. In such a case the following notational elements are employed: Unspecified Source State If the source STATE is unspecified, a small filled STATE symbol (a rectangle with rounded corners) is used as an icon.

Figure 42. Unspecified source STATE

Unspecified Target State If the target STATE is unspecified, a STATE rectangle surrounding a small filled STATE symbol is used as an icon.

Figure 43. Unspecified target STATE

Spontaneous Transition If no triggering event (i.e., no 'reason') is conceptualized and the TRANSITION is thus considered as spontaneous, no EVENT is depicted at all (as with the completion TRANSITION). To distinguish a spontaneous TRANSITION from a completion TRANSITION, the TRANSITION is marked with the the STEREOTYPE «spontaneous». Relevance Changes of state (the changes of and, hence, the transitions between the states are focused on, not the structure of source and target states) (cf. Section 6.9.).

Transition 5.2.2.

153

Complex transition

A complex TRANSITION 145 is a TRANSITION that "may have multiple source STATES and target STATES" (3-147). It represents a synchronization and/or a splitting of the flow of control into concurrent threads, without these necessarily being concurrent subSTATES of a COMPOSITE STATE. A complex TRANSITION is enabled when all the source STATES are occupied (and, if applicable, the corresponding EVENT occurs). After the TRANSITION has fired, all its target STATES are occupied (cf. 3-147). Notation A complex TRANSITION "includes a short heavy bar (a synchronization bar, which can represent synchronization, forking, or both [cf. also Section 4.3.6. ]). The bar may have one or more arrows from STATES [the source STATES] to the bar" (3-147). It also may have one or more arrows from the bar to STATES (the target STATES). "A TRANSITION string may be shown near the bar. Individual arrows do not have their own TRANSITION strings" (3-147). Example Figure 44 shows some course of action which consists of a beginning setup phase, a process phase, and a cleanup phase at the end. The process phase comprises two concurrent subprocesses which are entered at the same time. Both this transitional splitting as well as the synchronization before entering the cleanup phase are modeled by complex TRANSITIONS and hence with the synchronization bar.

A1

>j

A2

B1

·*>

B2

X*

Figure 44. Complex TRANSITION (3-148)

Relevance Changes of state that involve the splitting or synchronization of transitions.

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Advanced concepts of the UER

5.2.3. Transitions to and from composite states A TRANSITION to a COMPOSITE STATE is equivalent to a TRANSITION to its initial PSEUDOSTATE or to a complex TRANSITION to the initial PSEUDOSTATE of each of its concurrent regions, if the COMPOSITE STATE is one with concurrent regions (cf. 3-148). The entry action is always performed when a STATE is entered from outside. A TRANSITION from a COMPOSITE STATE indicates a TRANSITION that

applies to each of the subSTATES within the COMPOSITE STATE (at any depth) (cf. 3-148). "The TRANSITION is thus 'inherited' by the nested STATES. Inherited TRANSITIONS can be masked by the presence of nested TRANSITIONS with the same trigger" (3-148) (i.e., triggering EVENT). Notation A TRANSITION drawn to a boundary of a COMPOSITE STATE'S symbol indicates a TRANSITION to the COMPOSITE STATE. As this is equivalent to a transition to the initial PSEUDOSTATE(S) within the COMPOSITE STATE (regions), the initial PSEUDOSTATE(S) must thus be present in the COMPOSITE STATE (cf. 3-148).

"TRANSITIONS may be drawn directly to STATES within a COMPOSITE STATE region at any nesting depth. All entry actions are performed for any STATES that are entered on any TRANSITION. On a TRANSITION [into a COMPOSITE STATE with concurrent regions], TRANSITION arrows from the synchronization bar may be drawn directly to one or more concurrent STATES" (3-149). Any other concurrent regions start with their default initial PSEUDOSTATES (since no other starting STATES are specified in these cases, the default starting points of these regions are selected).146 A TRANSITION drawn from a boundary of a COMPOSITE STATE'S symbol indicates a TRANSITION from the COMPOSITE STATE. "If such a TRANSITION fires, any nested STATES are forcibly terminated and perform their exit actions, then the TRANSITION actions occur and the new STATE is established" (3-149). "TRANSITIONS may be drawn directly from STATES within a COMPOSITE STATE region at any nesting depth to outside STATES. All exit actions are performed for any STATES that are exited on any TRANSITION" (3-149). On a TRANSITION from within a COMPOSITE STATE with concurrent regions, TRANSITION arrows may be directly specified from one or more concurrent STATES to a synchronization bar (cf. 3-149). Since for the other regions no STATE is explicitly selected, specific STATES in these regions are irrelevant

Transition

155

to the firing of the TRANSITION (cf. 3-149), i.e., it does not matter which STATES of the other regions are occupied when the trigger occurs. The other regions are left as well when the specified source STATES are all occupied, the triggering EVENT (if any) occurs, and thus the TRANSITION fires.147 History Indicator "A STATE region may contain a [shallow] history indicator shown as a small solid-[outline] circle containing an Ή'. The history indicator applies to the STATE region that directly contains it" (3-149). A history indicator may have any number of incoming TRANSITIONS from outside STATES (cf. 3-149), but none from the STATE region that contains it (including the subSTATES of this region) or other concurrent regions. It has exactly one outgoing unlabeled TRANSITION, the target of which identifies the default history STATE, i.e., the first STATE to enter if the region has never been entered or the most recently occupied STATE has been the final STATE. Otherwise, if a TRANSITION to the history indicator fires, it indicates that the OBJECT resumes the STATE it last had within the region. Any necessary entry actions are performed. "The history indicator may also be Ή*' for deep history. This indicates that the OBJECT resumes the STATE it last had at any depth within the ... region, rather than being restricted to the STATE at the same level as the history indicator. A region may have both shallow and deep history indicators" (3149). If there is only one level of nesting, shallow and deep history are semantically equivalent. If there are more levels of nesting, shallow history remembers only the outermost nested STATE; deep history remembers the innermost nested STATE at any depth (Booch, Rumbaugh, and Jacobson 1999:302). Shallow and deep history indicators are both history PSEUDOSTATES. Example Figure 45 gives an example of a history indicator. The overall STATE machine starts with STATE A, since the TRANSITION from the initial PSEUDOSTATE has A as its target STATE. A is nested within a COMPOSITE STATE which contains the STATES A and B and TRANSITIONS between them. If the course of action in the COMPOSITE STATE is interrupted by the corresponding EVENT, STATE C outside the COMPOSITE STATE is entered. Due to the history indicator, a resumption of the course of action leads us back into the nested STATE the system has had last while within the COMPOSITE STATE. If the system had not been in the COMPOSITE STATE before, following STATE C STATE B would be entered first. Yet, since the initial PSEUDOSTATE forces the system to first enter the COMPOSITE STATE by way of entering A, this case cannot occur if the modeling

156

Advanced concepts of the U ER

as given in Figure 45 is comprehensive. If the system as displayed were part of another COMPOSITE STATE and additional TRANSITIONS lead a different way into the system, the latter case might, however, occur.

Figure 45. History indicator (cf. 3-150)

5.2.4.

Factored transition paths

By definition, a simple TRANSITION connects exactly two vertices in the STATE machine graph (cf. 3-151). However, since some of these vertices may be PSEUDOSTATES - which are transient in nature - there is a need fordescribing chains of TRANSITIONS that may be conceptualized as a single transition step. "Such a description is known as a compound TRANSITION" (3151).148 "As a practical measure, it is often useful to share segments of a compound TRANSITION. For example, two or more distinct compound TRANSITIONS may come together and continue via a common path, sharing its action, and possibly terminating on the same target STATE. In other cases, it may be useful to split a TRANSITION into separate mutually exclusive; that is, non-concurrent paths" (3-151). Both of these examples of graphical factoring in which some TRANSITION segments are shared result in simplified diagrams. "However, factoring is also useful for modeling dynamically adaptive behavior. An example of this occurs when a single EVENT may lead to any of a set of possible target STATES, but where the final target STATE is only determined as the result of an action ... performed after the triggering of the compound TRANSITION" (3-151). Note that the splitting and joining of paths due to factoring is different from the splitting and joining of TRANSITIONS described in Section 5.2.3.

Transition

157

The sources and targets of the factored TRANSITIONS discussed here are not concurrent. Notation Two or more non-complex TRANSITIONS emanating from different non-concurrent STATES or PSEUDOSTATES "can terminate on a common junction point. This allows their respective compound TRANSITIONS to share the path that emanates from that junction point. A junction point is represented by a small solid circle. Alternatively, it may be represented by a hollow diamond shape" (3-151) - the icon for decisions (cf. Section 4.3.6.). Two or more non-complex guarded TRANSITIONS emanating from the same junction point represent a static branch (cf. 3-151). "Normally, the GUARDS are mutually exclusive" (3-151). This is equivalent to a set of individual TRANSITIONS, one for each path through the STATE machine graph, whose GUARD condition is the conjunction of all of the conditions along the path. "Note that the semantics of static branches is that all the outgoing GUARDS are evaluated before any TRANSITION is taken" (3-152). A single junction point can be used to merge and split TRANSITIONS in a static branch. Two or more guarded TRANSITIONS emanating from a common (dynamic) choice point are used to model dynamic choices. In this case, the (normally mutually exclusive) GUARDS of the outgoing TRANSITIONS are evaluated at the time the choice point has been reached (cf. 3-152). The value of these GUARDS may be a function of and thus dependent on the actions of the incoming transition(s). A (dynamic) choice point is represented by a small hollow circle. In the case a junction point merging incoming TRANSITIONS is directly followed by a choice point, both are fused and the latter is used to represent both the junction point of the incoming TRANSITIONS and the choice point of the TRANSITIONS emanating from it. Examples Figure 46 shows a junction point that both merges and splits TRANSITIONS in a static branch. For example, a TRANSITION from StateO to States can only fire if event2 occurs. Addionally, b has to be less than 0 and a has to equal 5 (with a and b being two variables in the modeled system). Figure 47 shows a choice point that is fused with a preceding junction point and thus merges and splits TRANSITIONS in a dynamic choice. That is, triggered by event 1 and if the GUARD condition bsetzen
setzen
setzen
setzen
. Both AGGREGATIONS between the two participants are retained, the movement control and also the ATTACHMENT relation comprising movement propagation. That is, only instruments propagating their movements to the agent but being controlled in their movements by the agent are allowed. In particular, the movement propagation of the instrument towards the agent includes propagation of the manner of movement, which is reflected in the agent's movement. Accordingly, the movement of the agent is due to the horse instrument conceptualized to be leaping or 'horse-like'. Furthermore, because the movement (not the resultant location) is henceforth focused on, the goal location vanishes and is replaced by a ground location, giving way to a description and highlighting of the path along which the agent moves. The path relation rather than a position relation as in PUT (or more precisely, its SUBCORE STATE Localized) is the relation between the locational ineventity and the agent. Idiosyncratically, the ground ineventity is specified as an obstacle along (over or through) which the movement takes place. Thus, the role specification of the locational ineventity as ground is supplemented by an additional role ATTRIBUTE indicating that the ineventity is understood to be an obstacle in the represented eventity. In the final phase of this hypothesized development, the specificity of the agent (as a rider) and the ontological category of the instrument (as a horse) are abstracted away, leaving a leaping movement of the agent along a path. The path is characterized by a ground that is an obstacle, over or along or through which the path leads. The agent applies an instrument which prop-

Extensions of the prototypical case

319

agates its movements to the agent because of an ATTACHMENT relation between instrument and agent. Examples are (30a), with the instrument being explicitly specified as a horse, and (30b), where the instrument is left unspecified and has to be inferred from the context (the context allows to reconstruct the instrument as a horse). Finally, TRAVERSE as a parent of both LEAP and CROSS does not necessarily include the leaping manner of the movement (although LEAP does, cf. below), as can be seen in the examples in (31). The proposed UER representation for the general TRAVERSE is depicted in Figure 103.

1 =πί

-j / Instrument: Ineventlty

|

{propagation . movement)

•apply-

Υ attachment»

ι Γ

{control * movement)

/ '

/

HZ]] / Ground : Ineventlty

[[*D / Agent: Ineventlty

«role» specification = obstacle

.-do·

ι I

*

when (location t z->tocation)

Figure 103. TRAVERSE-eventity

Compare the representation of TRAVERSE in Figure 103 with the representation of PUT in Figure 94 on p. 283. Of the prominent participants of PUT, only the agent is left in TRAVERSE280 - embodying the TRANSITION of the undergoer as a result of the semantic changes. This leads to a dynamic modeling that is structurally similar to SICHJSETZEN, but the focus shifts from passivity to activity: there is only one prominent participant left, whose PARTICIPATE ASSOCIATION is marked by «do». The focus changes from the resultant state to the ASS: in PUT, the resultant state is specified as a SUBCORE STATE Localized and the ASS is unspecified,

320

Application II: The polysemy of German >setzen
setzen
invert» (ero*·, leap): An Idiosyncratic development with a horse as undergoer (becoming an instrument) might be the cause (or the additional readings. The focus shifts from passivity to activity.

leap ·> merejMp: The ffistniment and its relations are lost.

The instrument participant can be underspecified in this frame.

Figure 106. Overview of the discussed readings of setzen

324

Application II: The polysemy of German >setzen
l

label

label

Figure 140. SUBMACHINE STATE (with stub STATES)

StateName

Dynamic structure elements

Subcore State

«subcore» StateName [A / Role, B / Role]

Figure 141. SUBCORE STATE

Swimlane /

X

Swimlane 1

Swimlane 2

Figure 142. SWIMLANE

Unspecified Source and Target state

Figure 143. Unspecified Source STATE

Figure 144. Unspecified Target STATE

349

350

The notational elements of the UER

A.4.

Eventity frame and eventity frame template

Eventity Frame

staticPeriphery eventityFrame dynamicCore '

Figure 145. EVENTITY FRAME

Eventity Frame Template i_Parameters

eventityFrame

Figure 146. EVENTITY FRAME TEMPLATE

Participant Class [[representative]] / Role : Type attributes Figure 147. PARTICIPANT CLASS

Miscellaneous

351

Style Guidelines: - Center PARTICIPANT CLASS specification in boldface. - If any, center keyword (including STEREOTYPE names) in plain face within guillemets above specification. - Begin PARTICIPANT ROLE and PARTICIPANT TYPE with uppercase letters. - Left flush ATTRIBUTES in plain face. - Begin ATTRIBUTE names with a lowercase letter. - Show abstract elements of the PARTICIPANT CLASS specification in italics (this can be either the PARTICIPANT REPRESENTATIVE, the PARTICIPANT ROLE, or the PARTICIPANT TYPE, two of them, or all three). - If a PARTICIPANT CLASS is the child of another PARTICIPANT CLASS, only those elements in its specification which have not been specified in the parent declaration (or are abstract elements in the parent PARTICIPANT CLASS) have to be shown. The others will automatically be inherited from the parent.

A.5.

Miscellaneous

Note Note

Figure 148. NOTE

Unspecified String Element The underscore (' ') can be used in all cases in which a string element is not specified, e.g., for type declarations, names, the binding of TEMPLATE parameters etc.

Notes

Chapter 1. 1. Event variables were introduced by Davidson (cf. Davidson 1980). Therefore, approaches using event variables are nowadays called Davidsonian. Those who follow Davidson in representing eventities as arguments in logical structures, but depart from him by separating participants and the semantic roles, are representatives of neo-Davidsonianism. 2. Cf. the Discourse Representation Theory (Kamp and Ryle 1993) and the Conceptual Graphs (Sowa 1984,2000a). Both are graphical formalisms that can be mapped to predicate logic, and both support that non-linear representations are more intuitive. Chapter 2. 3. Cf., e.g., Burg and Riet (1994,1995a, 1995b, 1995c, 1995d, 1996, 1997,1998); Helbig (2001); Lytinen (1992); Riet, Burg, and Dehne (1988); Schank (1972, 1973); Schank and Abelson (1977); Sowa (1984, 1988, 1991, 1992a, 1992b, 1993, 2000a, 2000b); Sproat (1985); Wilks (1973, 1977); Wilks and Pass (1992). 4. Concerning the prototypical emergence of eventity concepts through experience, we follow Avrahami and Kareev (1994). They propose the cut hypothesis (and support it by convincing experiments): "A sub-sequence of stimuli is cut out of a sequence to become a cognitive entity for someone, if it has been experienced many times, with different sub-sequences preceding and following it on the various occasions" (1994:245). 5. Also, pure syntagmatic approaches to verbal semantics are not considered. 6. This is not to say that it might not be possible to extend the UER to include these investigational areas, but it is necessary to straighten the focus of this book. 7. Note that Putnam's final conclusion is that meanings cannot be explicated. Nevertheless, he keeps the notion of meaning as such. The philosophical considerations leading to such a conclusion will, however, not be treated here - the interested reader is referred to Putnam's work. 8. There are different conceptions of the term semantic marker which are not to be confused with the specification of the term in Putnam's approach. Cf., for example, Lakoff (1976:44): "One meaning of the word bachelor might be represented by the following set of elements: (animate), (human), (male), [never married]. The first three elements are 'semantic markers'. These occur repeatedly throughout the language. The last is called a 'distinguisher'." 9. Cf. Geeraerts (2002:285): "Prototypical categories cannot be defined by means of a single set of criterial (necessary and sufficient) attributes."

354

Notes

10. It is not obligatory within prototype theory that there is only one prototype per category. Prototypes are usually identified by judgements of informants. 11. For an overview of different positions in linguistics, cf. Taylor (1989). For a treatment of the verb lie within prototype theory, cf. Coleman and Kay (1981). 12. Although we are not focusing on denotation, prototype theory is closely linked to such questions, because whether an entity is considered to be a denotation of a particular lexical item by a speaker depends on sufficient similarity (Aitchison 1994:55) between that entity and the prototype. 13. Differences between the 'standard prototype theory* and the 'extended prototype theory' (cf. Gansel 1996, Kleiber 1993) are not explicated in this brief description. 14. It is not only the respective roles the participants play in the eventity which are important in representations of verbal semantics, but also the properties they need to have in order to function as participants in a particular eventity (e.g., in order to be able to wake up an entity, this entity has to be animate). These properties are dubbed seleciional restrictions and are represented in the UER by ATTRIBUTES (cf. Section 6.3.). 15. Since it is not possible to offer a comprehensive treatment of the work that has been done on semantic roles, cf. Dowty's overview in Dowty (1991), Engelberg's (2000) treatment of contemporary approaches, Ravin's (1990) discussion of semantic roles, and also Chierchia (1989); Dowty (1989); Frawley (1992); Grimshaw (1990); Jackendoff (1972,1987,1990); Lyons (1977b); Premper (2001); Primus (1998); Rauh (1988), amongst others, for discussions on the subject. 16. Note that the fifth property of each of the two sets is the most controversial. 17. Dowty specifies an incremental theme by a homomorphism between the denotation of an argument y (where y is the incremental theme) and an event e\ a homomorphism which preserves the 'part-of' relation: "If χ is part of y, then if a telic predicate maps y (as Theme) onto event e, it must map χ onto an event e' which is part of e" (Dowty 1991:567). Cf. also Section 6.13. 18. However, we will discuss neither the above properties in detail - for a discussion and elaboration of Dowty's proposal, cf. Primus (1995, 1998) - nor their intended semantic independency, nor the argument selection principle Dowty establishes. 19. Note that combinations of the above mentioned properties may correspond to familiar role types, as Dowty states: "AGENT is volition + causation + sentience + movement, or in some usages just volition + causation, or just volition (Dowty 1979), or, according to the ordinary language sense of 'agent' causation alone. EXPERIENCER is sentience without volition or causation. INSTRUMENT is causation + movement without volition or causation" (Dowty 1991:577). 20. For a treatment of the terms aspect and Aktionsart and the fact that they "have received no universally accepted definitions" (Binnick 2001:561), cf. Binnick (2001:561-565). 21. For an overview of classifications proposed in the literature, cf. also Chapter 2

Notes

22. 23.

24.

25.

26.

27.

28.

29.

355

in Verkuyl (1996), and for an overview of more formal classifications cf. Krifka (1989), Chapter 2.2. Cf. also Dowty (1979) for his further development, the aspect calculus. The tests will not be discussed here. The interested reader is referred to Vendler (1967b) or, e.g., Dowty (1979); Krifka (1989); Rapp (1997); Wanner (1999). Verkuyl terms these features [± Definite] and [± Process] (cf. Verkuyl 1996: 35). For a more concise discussion of Vendler's classification, cf. Dowty (1979); Rapp (1997); Verkuyl (1996). Aktionsart and verb classification are often discussed together with 'formal event structures' (for example, cf. Rapp 1997:18) or 'event semantics'. Some works in this line are Barwise and Perry (1983); Davidson (1980); Dolling and Zybatow (2001); Higginbotham, Pianesi, and Varzi (2000); Landman (2000); Lepore and McLaughlin (1985); Parsons (1990); and Tenny and Pustejovsky (2000b), amongst others. Different definitions of the term lexeme can be found in the literature, including that of a family of lexical units sharing the same lexical form; where lexical form and lexcial unit are understood in Cruse's way: "we may call the abstract unit of form which is realised in actual sentences as the appropriate member of a set of word forms differing only in respect of inflections a lexical form;... A lexical unit is then the union of a lexical form and a single sense" (Cruse 1986:77). Although we are using Cruse's terms of lexical unit and lexical form, we are not following his lead in regarding lexical units to be the primary semantic units (and thus the lexeme to be solely a union or family of the former without having its own identity). Instead, we view the lexeme to be the primary semantic unit, where lexical unit and lexical form are mere technical terms, i.e., we understand a lexeme as an abstract lexical form together with the different senses which are attributed to it. It is our feeling that this view is supported in that lexical units forming a polysemous lexeme are intuitively understood as belonging together and forming one 'whole'. The second case of lexical ambiguity (besides polysemy), namely homonymy, is not treated in extenso, as homonymy is not a structural relationship, but two different readings just happening to share one lexical form. Croft (1990) points out the homonymy's right of existence as being economic: "Homonymy represents paradigmatic economy: minimizing the number of morphemes, by giving them several meanings" (Croft 1990 166). Cruse (1986:268) rightly indicates the impracticability of proving that two items are absolute synonyms: one would have to check their relations in all conceivable contexts. From the theoretical point of view this is impossible, given the infinite number of possible contexts. But a falsification of absolute synonymy is in principle straightforward. A semantic component is, according to the glossary, a potentially contrastive part of the meaning of a lexical unit. It is thus a notion which comes close to the one of semantic features. For a discussion of antonymy, cf., e.g., Cruse (1992) and in particular Cruse and

356

30. 31.

32. 33.

34. 35.

36.

37.

38. 39. 40. 41. 42.

43. 44.

Notes Togia (1995). A lexeme is autoantonymous, if one of its readings (i.e., lexical units) is antonymous to another. A lexeme is autohyponymous, if one of its readings is hyponymous to another. The difference between meronymy and meronomy, i.e., the difference between the part-whole sense relation of lexical units and the conceptual part-whole relation, is unfortunately often neglected in the literature. A lexeme is automeronymous, if one of its readings is meronymous to another. In WordNet, synonymy is understood more broadly than just as identity in meaning. Thus, the synsets (which are the nodes in the net) are equivalence classes established by a similarity relation. In this regard, the approach is similar to the mental picture approach in prototype theory. Polysemy as a systematic variation of senses is rather the rule than the exception in the lexicon. That is, monosemy (i.e., a (1:7)-relation) is the marked case, whereas polysemy is the unmarked (cf. Zaefferer 2002b). For a different conception, which can probably not be supported by native speakers' intuitions, cf. Ruhl (1989). Ruhl argues that lexemes should be presumed initially to be monosemic, having a single, highly abstract meaning. Only if the search for a unitary meaning fails, one should resort to polysemy. On this discussion and on other issues concerning polysemy, cf. also Behrens (2002). "WordNet does not distinguish between polysemes and homonyms. On the other hand, many cases of regular and predictable polysemy are grouped together to indicate the close semantic relation of the different senses" (Fellbaum 1998b). In contrast to that, polysemy is called irregular, if the semantic distinction between a, and aj is not exemplified in any other word of the given language (Apresjan 1974:16). Whereas Dowty (1979) calls the method lexical decomposition, Parsons (1990) speaks about subatomic semantics. "According to this view, the meaning of lexical items is an unanalysable whole that cannot be decomposed into smaller components in any systematic way" (Bierwisch and Schreuder 1992:28). I would like to thank Dietmar Zaefferer for bringing the following points to my attention. The cited article was first published in 1968, and supplemented by significant endnotesin 1976. For further discussions on Generative Semantics in general, cf., amongst others, Abraham and Binnick (1972); Bach (1968); Binnick (1972); Immler (1974); Lakoff (1965,1971 a, 1971b, 1976); Lakoff and Ross (1976); McCawley (1968, 1976b); and for the historical perspective Newmeyer (1980,1996). The grammatical tense of the surface structure is not taken into account by McCawley. According to Rapp, DO is a basic predicate (taking individuals as arguments), whereas BECOME and CAUSE are complex predicates ("Funktoren" [functors]), which take other predicates as arguments.

Notes

357

45. Note that Lakoff (1976) already introduces a semantic feature [±DS] ("do something") which in the positive case marks verbs as representing activities (Lakoff 1976:50). 46. "Die Paraphrasebeziehungen, auf denen die Theorie der lexikalischen Zerlegung aufbaut, gelten immer nur annähernd; die semantische Repräsentation einer lexikalischen Einheit durch semantische Atome gibt die Bedeutung dieser Einheit niemals in allen Einzelheiten genau wieder" (Immler 1974:165). [The paraphrase relations the theory of lexical decomposition is based on always hold only approximately; the semantic representation of a lexical unit through semantic atoms never reflects the meaning of this unit exactly in all details.] Cf. also Bartsch and Vennemann (1972:21): "the alleged equivalences between the meaning of the decomposed lexical items and the meaning of the proposed decompositions never hold." This point is also taken up by Wierzbicka (1975), who notes some phenomena linked with this objection in more detail. 47. VPs and verbs are supposed to correspond to Events, NPs and nouns to Things, PPs and prepositions to Places or Paths, and APs and adjectives to Properties (cf. Wunderlich 1996b: 170). Cf. also Jackendoff (1992:200). 48. Note the importance that is attributed to goals, as each path is described by a function of "the point at which motion terminates" (Jackendoff 1991:13). This exclusiveness has been abandoned later on, cf. (5b) on p. 42, where source, path and goal are included as possible path-functions. Yet we believe in a primacy (although not exclusiveness) of the goal in human conceptualization. This is supported by neuropsychological experiments, cf., e.g., Hommel et al. (2001) and Gallese and Metzinger (2003). The issue will be resumed at several points in this investigation and will gain a particular importance in Chapter 8. 49. Jackendoff never claims to have a complete list of functions, but: "The important thing is that there should be a rather small set of state- and event-functions and a rather small set of place- and path-functions involved in the description of any semantic field of events and states, among which are the fundamental functions GO, STAY and BE" (Jackendoff 1983:204). 50. Whereas the CHANGE-function includes initial and final states (but no path), the Go-function allows for inital or final state or path, but only one of them at a time; a theoretical limitation that seems to be too strong (cf. also Example (8) on p. 45). 51. "If there is any primacy to the spatial field, it is because this field is so strongly supported by nonlinguistic cognition; it is the common ground for the essential faculties of vision, touch, and action. From an evolutionary perspective, spatial organization had to exist long before language" (Jackendoff 1983:210). 52. "Prinzipiell gibt es zwei Arten, Verben in thematischer Hinsicht zu beschreiben. Eine Möglichkeit ist, ihre Argumente in semantische Gruppen (z. B. Agens, Patiens etc.) einzuteilen. Der alternative Ansatz besteht darin, jedem Verb durch Dekomposition eine spezifische semantische Struktur zuzuordnen - die Argumente des Verbs sind in diesem Fall durch ihre Position bei den sublexikalischen Prädikaten definiert. Während im ersten Falle also dem Verb ausgehend

358

53.

54.

55.

56. 57. 58. 59.

Notes von den Argumenten eine thematische Struktur zugeordnet wird, werden im zweiten Falle umgekehrt die Argumente durch die sublexikalische Struktur des Verbs charakterisiert. In der Literatur wird der erste Ansatz als predicate independent approach bezeichnet, der zweite Ansatz als predicate dependent approach (Levin 1985:51)" (Rapp 1997:9). [In principle, there are two methods to describe verbs thematically. One possibility is to group their arguments in semantic categories (e.g. agent, patient etc.). The alternative approach is to assign a specific semantic structure to each verb by decomposition - the verb's arguments are in this case defined by their position in the sublexical predicates. While in the first case the arguments are taken as a starting point and a thematic structure is assigned to the verb, in the second case the arguments are conversely characterized by the verb's sublexical structure. In the literature, the first approach is called predicate independent approach, [and] the second approach is called predicate dependent approach.} Nevertheless, he complains that "there is (oddly enough) no standard name for the second argument of CAUSE, the caused Event" (Jackendoff 1987:378). Thus, although proposing a predicate dependent approach, he criticizes the lack of a notion for a semantic role of an eventity, the caused eventity. In (1987), the preliminary function ACT has been introduced for both volitional or non-volitional acting of the actor on the patient. The feature VOL is added to ACT if volitional acting is involved. In the overall semantic representation the feature is added to the function representing the acting as such and not to the representation of the participant. This is problematic, because volitionality is, of course, a characteristic of a participant and not of an element of dynamic structuring. Later, when Jackendoff notices that a larger vocabulary of functions would be necessary on the action tier (Jackendoff 1987:398) if the semantics of ACT was being kept as narrow as this, he abandoned ACT and substituted it by AFF, a general function relating actor and patient, or, in our terms, identifying the macroroles actor and undergoer within his functional approach. Cf. Jackendoff (1987:395,1990:127), with corrections by the author in the thematic tier representation in (7b). Subscripts on functions of the thematic tier are omitted in this representation. The function INCH maps a state into an event to represent inchoatives. That is, besides other supplementary functions, Jackendoff (1990) introduces a function relating to temporal structure and Aktionsart. Besides the coarse-grained representation of the temporal tier, questions of adverbial modification or inference that Jackendoff treats are not taken into account. "We can now use the temporal tier to correlate subevents in the thematic and action tiers" (Jackendoff 1987:399). We will neither discuss the existence of a function MOUTH OF nor the construction of the thematic tier of drink, although both would in other contexts be worth a detailed investigation. Note that the feature [± CONTACT] is a feature of functions again, although it describes a relationship between two participants.

Notes

359

60. After failing to model non-change eventities (Ravin 1990:84) in the 1980s, Jackendoff heads at modeling the Vendler classes (1991:39). 61. The Grammatical Constraint restricts Conceptual Semantics at least in some respects to particular languages. In order to avoid this, we will try to approach the problem of semantic representation from the other, the conceptual side, because - as Jackendoff states to support the one-level approach - "semantic structure is the same level of representation as conceptual structure. Therefore, any theory of the semantic structure of language is ipso facto a theory of the structure of thought" (Jackendoff 1983:209). 62. Fillmore intends the term frame as a general cover term for the set of concepts variously known in the literature as schema, script, scene, cognitive model and the like. Cf. Fillmore (1982: 111, 1985:223) for further citations of work employing a similar notion. Moreover: "In the early papers on Frame Semantics, a distinction is drawn between scene and frame, the former being a cognitive, conceptual, or experiential entity and the latter being a linguistic one" (Petruck 1996:1; cf., e.g., Fillmore 1977b). In later works, the notion scene ceases to be deployed and frame is used in the sense introduced here. 63. Thus, presuming a given frame, it is possible to demonstrate which clusters of concepts are open to lexicalization in a particular language. Nevertheless, the task of adequately delimiting a frame remains problematic. 64. For a more detailed discussion of the differences between lexical fields and frames, cf. Fillmore (1985:226-230). Note that in Johnson et al. (2001: 11) the relation between a frame and a word is compared to the distinction between Langacker's (1987) terms base and profile. 65. The notion of frame element instead of semantic or thematic role has been introduced for several reasons: "First of all, there are too many different semantic relations to fit into any of the 'standard' listfs] of thematic roles or case roles. We are in the process of preparing a more serious answer to this question that will show examples of (a) frames that involve multiple inheritance, (b) frames that involve complex temporal structures in which a single entity might be participating in one role in one phase and another role in a later phase, (c) frame elements that defy any non-arbitrary parceling out into any of the familiar thematic roles or even any of the augmented lists (John Sowa etc.), and so on" (Question 13 in the FAQ section at http://www.icsi.berkeley.edu/~framenet/FNfaqs.html, accessed on January 28,2004). 66. In the frame description the payment is characterized by the less appropriate category 'money', which does not indicate a role, but at best an ontological category. Moreover, 'money' is not the sole form of payment applicable in commercial transactions nowadays. 67. FrameNet has primarily lexicographical purposes, whereas the original conception of frame semantics was a lot broader: "One of the goals of the kind of frame semantics that I am speaking for is that of having a uniform representation for word meanings, sentence meanings, text interpretations, and world models" (Fillmore 1976:28).

360

Notes

68. Cf. also Stein: "Dagegen ist die Zuordnung von SF und CS ... ein problematischer Punkt, den Lang selbst als 'höchst unklar' bezeichnet" (1999:29). [By comparison, the correlation of SF and CS is ... a problematic point which Lang himself calls 'highly unclear'.] 69. A similar approach is adopted by others as well, cf., e.g.: "Meine eigene Klassifikation, bei der Verben ebenfalls durch die Methode der sublexikalischen Dekomposition charakterisiert sind, wird dagegen in eindeutiger Weise restriktiv sein: Die semantische Beschreibung dient ausschließlich einer grammatikalisch relevanten Klassifikation - folglich werden nur syntaktisch bzw. morphologisch wichtige Merkmale in der semantischen Struktur repräsentiert" (Rapp 1997:15). [My own classification, in which verbs are also characterized by the method of sublexical decomposition, will by contrast be restrictive in an unambiguous way: the semantic description exclusively serves a grammatically relevant classification - accordingly, only syntactically or morphologically relevant features are represented in the semantic structure.] 70. Cf. the conditions Kaufmann proposes: "Kl: Partizipanten innerhalb einer Situation müssen in einer inhaltlich spezifizierten Beziehung zueinander stehen. K2: Teilsituationen müssen kausal miteinander verbunden sein" (Kaufmann 1995:201). [Kl: participants within a situation have to be related to each other in a way specified by content. K2: sub-situations have to be connected causally.] 71. Pustejovsky expects sense enumeration lexicons (SELs) to enumerate different senses for words like, e.g., fast to account for the ambiguity which is illustrated in expressions like a fast typist, a fast decision, a fast game (Pustejovsky 1995:44). Concerning this issue, we completely endorse Behrens' view: "Note, however, that it does not follow from this that real dictionaries would actually apply the criticized 'sense enumeration strategy' in all the cases discussed by Pustejovsky. In fact, a substantial part of the relevant examples are not recognized by lexicographers as 'polysemous' and so coded in distinct entries or subentries" (Behrens 1998:113-114). 72. Accordingly, dot objects or dotted types and corresponding mechanisms introduced by Pustejovsky as part of his qualia structure are not discussed either. 73. True adjuncts (as their name indicates) are in fact no arguments at all. 74. In the UER, a potential way of accounting for participant differences similar to those proposed by Pustejovsky is to introduce suitable STEREOTYPES for PARTICIPATE ASSOCIATIONS. Cf. Sections 4.1.4., 5.4.3., and 6.13. 75. In Section 2.1.2.2., four verb classes were distinguished. Following Pustejovsky, these classes "collapse to three distinct structural configurations, where transitions subsume both accomplishments and achievements" (Pustejovsky 1991b: 56). This also entails that Pustejovsky's term process does not describe all of those eventities Vendler terms process, but solely corresponds to Vendler's term activity - as Rapp has already noted (cf. Rapp 1997:25). 76. The conjunctions used in LCS'-representations indicate the simultaneity of the conjuncts.

Notes

361

77. Moreover, Pustejovsky introduces a mechanism to parameterize eventities according to the 'event headedness' of their subeventities. With 'event headedness', Pustejovsky provides a way of indicating the foregrounding or backgrounding of event arguments (Pustejovsky 1995:72). "This offers him a way of dealing with verbal alternations" (Behrens 1998:109) and thus of capturing syntactic reflexes, which do not lie within the focus of this work. 78. That is, the process temporally precedes the state, each is a logical (whatever this may mean) part of the eventity encoded by build, and there is no other subeventity that is part of that eventity. 79. "The ability of a lexical item to cluster multiple senses" (Pustejovsky 1995:91) is what is referred to as a Icp. 80. However, Pustejovsky's qualia structure predicates need interpretation. Even if we assumed some kind of predicate dependent approach, such as first mentioning the subevent the quale relates to (as indicated by the predicate name e) and then the agent, we are still in need of an appropriate interpretation for [T] in the agentive quale's build .act predicate in (19). 81. Further work in the Generative Lexicon framework includes, amongst many others, Asher and Pustejovsky (2000); Bouillon and Busa (2001a); Busa, Calzolari, and Lend (2001); Pustejovsky (1988, 1993,1998,2000a, 2000c, 2000b, 2001a, 2001b, 2001b, 2002); and Pustejovsky and Bouillon (1996). For critical reflections, cf., e.g., Behrens (1998); Fodor and Lepore (2001); Schuster (1999); Stein (1999); Wunderlich (1996b). 82. Cf. http://www.une.edu.au/arts/LCL/disciplines/linguistics/nsmpage.htm for the NSM homepage (accessed on January 28,2004). 83. Goddard and Wierzbicka are the most prominent representatives of the NSM approach, cf. some of their work: Goddard (1989a, 1989b, 1994, 1998, 2000, 200la, 200Ib, 200Ic, 2002a, 2002b); Goddard and Wierzbicka (1994, 2002a, 2002b); Harkins and Wierzbicka (2001); and Wierzbicka (1972, 1975, 1980, 1989a, 1989b, 1992a, 1992b, 1994, 1995, 1996, 1998, 2000a, 2000b, 2000c, 2001,2002). 84. As, for example, expressed in Fabb (1985). 85. Notice that, if the canonical contexts are not constituted of primitives exclusively, they strictly speaking do not lie within the NSM any more. 86. This explication is a case of a 'predominant' but not 'exclusive' composition of primitives, as else and me, for example, are not lexemes of the minilanguage. In order to account for that, these elements are treated as 'allolexes' of the primes OTHER and I (Goddard 2002b: 20). Chapter 3. 87. The considerations about the notations! foundation of the UER are adopted from the UML specification, cf. OMG (2001:3-6-3-7). 88. This conforms to the criterion of cognitive adequacy on the one hand and supports the choice of using an object-oriented approach on the other hand, where objects with their characteristics, behavior and interactions are the focus.

362

Notes

89. Generally, one could say that all UML-constructs can be used in the UER. Doing so does not normally cause any ill-formedness (as long as not otherwise noted in the presentation of the UER). But it is assumed that not all of the UML-constructs are necessary in the UER, so some constructs have been omitted in the presentation of the UER. Admittedly, some of the presented concepts may however seem superfluous at first glance, but as an applicability cannot be ruled out at the present stage of the development of the UER and as extensions of the UER's application domain might make use of these concepts, they are nevertheless introduced. 90. In some relationships (such as aggregation and generalization, cf. below), several paths of the same kind may connect to a single symbol. In these cases, the line segments connected to the symbol can be combined into a single line segment, so that the path from that symbol branches into several paths in a kind of tree. This is purely a graphical presentation option; conceptually the individual paths are distinct (cf. 3-7). 91. This notation is not applied for keywords used to distinguish EVENT types. These are shown directly within the EVENT expression, cf. Sections 4.3.8. and A.I. Chapter 4. 92. The notion of PROPERTY as used in the UER differs from the UML's one. 93. This does not hold for, e.g., the secondary characteristics for the different AGGREGATION subtypes which still remain to be established, cf. Section 5.1. 94. Meta-ATTRiBUTES have, as ATTRIBUTES do, a MULTIPLICITY, cf. Section 4.2.2. 95. {abstract} specifies that the model element the PROPERTY string is attached to cannot be directly instantiated and thus needs to be a super-element of other non-abstract model elements (cf. Section A.I.). 96. On the concept of inheritance, GENERALIZATION, cf. Section 4.2.10. 97. A classification hierarchy of STEREOTYPES can be displayed on a UML CLASS diagram (cf. 3-32, 3-57-3-59). 98. For a list of predefined keywords and STEREOTYPES, cf. Section A. 1. 99. As PROPERTIES are meta-ATTRiBUTES, the PROPERTY definitions in a STEREOTYPE declaration are given according to the ATTRIBUTE specification format, cf. Section 4.2.2.: name ':' type-expression '[' multiplicity ']'. This specifies PROPERTIES that a model element branded by the STEREOTYPE can have. 100. A data type is similar to a CLASS, but its instances are primitive values (rather than OBJECTS). For example, particular Integers and strings are treated as primitive values. A primitive value does not have an identity, so two occurrences of the same value cannot be differentiated. 101. For a special kind of CLASSES in the UER, the PARTICIPANT CLASSES, cf. Section 5.4.2. 102. Cf., for example, the STEREOTYPE declaration in Section 4.1.4.

Notes

363

103. For ENUMERATION types see Section 4.1.5. Boolean is an ENUMERATION type with only two possible values, namely 'true' and 'false'. 104. A MULTIPLICITY of 0.. 1 theoretically provides for the possibility of null values: the absence of a value, as opposed to a particular value from the range. 105. Concerning the value-expression, the UER specification differs from the UML specification. In the UML, the value-expression is an expression specifying the value of the ATTRIBUTE upon initialization. That is, if an instance is initialized, the ATTRIBUTE holds this value unless it is superseded in an explicit construction of the instance. It is a constructive approach. The UER, in contrast, starts from the opposite assumption, by assuming the prior existence of instances. Therefore, the instance's membership in the CLASS has to be observed. That is, the UER follows a 'deconstructive' (in a decompositional sense) approach. 106. A binary ASSOCIATION is a special case with its own notation. 107. Cf. Section 4.2.5. The size of the diamond has no semantic significance, as the notation as a connective of ASSOCIATION path segments is unambiguous. For the sake of clarity, however, the ASSOCIATION diamond and the AGGREGATION indicator are differently sized. 108. The xor-CONSTRAINT for associations is a special case of the general xorCONSTRAINT, cf. Section A.I. 109. When referring to the ASSOCIATION ends of a binary ASSOCIATION in the following descriptions, the target end is the one whose PROPERTIES are being discussed. The source end is the Other' end. 110. When placed on a target end in a binary ASSOCIATION, MULTIPLICITY specifies the number of target instances that may be associated with a single source instance across the given ASSOCIATION. MULTIPLICITY for an n-ary ASSOCIATION may be specified, but is less obvious than binary MULTIPLICITY. The MULTIPLICITY on an ASSOCIATION end represents the potential number of instance tuples in the ASSOCIATION when the other n-1 values are fixed. 111. Not all possible ranges appear to be relevant for the application domain of the UER. In order not to be too restrictive, no explicit limitations are given. Nevertheless, in most cases MULTIPLICITIES of 1 (which can be omitted as default value in most cases) and 0..1 can be expected. 112. For a list of predefined CONSTRAINTS and their definition cf. Section A.I. 113. The connection between a NOTE or CONSTRAINT and the element it applies to is shown by a dashed line without an arrowhead. This is not a DEPENDENCY. 114. Semantic refinements are expressed by GENERALIZATIONS. 115. Statechart diagrams represent the behavior of an entity capable of dynamic behavior by specifying its response to the receipt of EVENT instances. An activity diagram shows the flow of control. It is a graph that represents a special case of a STATE machine, and it is used to model processes. 116. The eventity ontology is not to be confused with the participant ontology outlined in Section 6.5. 117. A third variant may be used to evade the use of the anchors, by displaying internal TRANSITIONS as self TRANSITIONS (i.e., the arrow emanates and ends

364

118.

119. 120. 121.

122.

123. 124.

125. 126.

127. 128. 129.

130.

Notes on the STATE'S boundary) with the additional keyword «internal» for internal TRANSITION. The burden of distinguishing internal TRANSITIONS from self TRANSITIONS is then put upon the keyword which is worse than using a graphical difference to mark different concepts. Therefore, we advise users of the UER to use this third variant as sparsely as possible, e.g., only if a tool does not enable the second alternative. Even if there are internal TRANSITIONS (which thus include actions of the OBJECT), the OBJECT is still in a PSS, because internal TRANSITIONS comprise 'side-actions' which are not in the modeling focus. This notation is reminiscent of the action state notation in UML, cf. 3-159. The notation for these is similar to the stubs used for stubbed TRANSITIONS and stubbed SIGNALS, cf. Sections 5.3.1. and 5.3.2. A pathname specifies the path from the top modeling level of the invoked SUBMACHINE, listing the nested STATES top-down and separating them by the pathname separator ('::' in the UER). The same applies to history PSEUDOSTATES and to final STATES: only the regions of a COMPOSITE STATE with concurrent regions may have a history or final STATE, but not the COMPOSITE STATE itself. Although no synchronization is expressed, the symbol is nevertheless employed for both create and destroy PSEUDOSTATES. A chain of decisions may be part of a complex TRANSITION, but only the first segment in such a chain may contain an EVENT trigger label. All segments may have GUARD expressions. This notation is reminiscent of the final state notation of finite automata. In the UML, EVENTS are always assumed to take place at an instant in time with no duration. In the UER, however, continuous SIGNAL EVENTS can be modeled and are required in particular cases (cf. also Section 6.10.). Strictly speaking, the term 'EVENT' is used to refer to the type and not to an instance of the type. However, on occasion where the meaning is clear from the context, the term is also used to refer to an EVENT instance (cf. 2-150). A signature is a string that indicates the name and the arguments of, e.g., a SIGNAL reception. Cf. Sections 5.2.1. and A.I. A continuous SIGNAL requires the marking of the SIGNAL sending time as unspecified. An additional CONSTRAINT on both SIGNAL and triggered TRANSITION may specify parallelism of both, in particular coincident endpoints. Although in general possible, only rarely will a modeling of sending SIGNALS as exit actions occur. It is more sensible to model these as actions of the TRANSITION triggered when the STATE is left.

Chapter 5. 131. The term participant is understood in a very broad sense. It includes not only prototypical participants in agent or experiencer roles and the like (as often held by ineventities), but also other semantic 'factors' that bear roles such as

Notes

132.

133.

134. 135.

136.

137.

138. 139.

140.

141.

365

instrument or goal. Cf. also Section 6.6. The development of the UER's AGGREGATION has been inspired by Artale et al. (1996); Barbier et al. (2001); Chaffin (1992); Cruse (1979, 1986); Gerstl and Pribbenow (1995, 1996); Henderson-Sellers and Barbier (1999a, 1999b); Iris, Litowitz, and Evens (1988); Lyons (1977a); Saksena et al. (1998); and Winston, Chaffin, and Herrmann (1987). The interested reader is also referred to Markowitz, Nutter, and Evens (1992); Moltmann (1996, 1997); Pianesi (2002) (a review of the latter); and Simons (1987). The notions of primary (essential) vs. secondary (non-essential) characteristics were introduced by Saksena et al. (1998:273). In their paper on meronomic relationships (the aggregation concept in the UML), lifetime binding was considered a primary characteristic as well, as "the lifetime of the part must overlap the lifetime of the whole" (Saksena et al. 1998:275). Note that the UER's AGGREGATION concept as such has a much broader scope than meronomic relations alone. Meronomic relations are introduced as the MERONOMY subtype of the UER's AGGREGATION in Section 5.1.1. Also note that secondary characteristics are introduced only for subtypes of AGGREGATION, not for the general AGGREGATION concept itself. This characteristic is adopted from Henderson-Sellers and Barbier (1999a), who also work on the UML's aggregation and thus meronomic relations. In the following, AGGREGATION instances will also be called AGGREGATIONS, as it is clear from the context whether a relation is one between two CLASSES or between two OBJECTS. The ENUMERATION literals of Propagation and Control could not be fully specified to date. We have to rely on an incremental definition based on typological studies which have to be carried out in order to determine the sets of relevant semantic features. As we assume that not all semantic features which might be controlled might also be propagated, we introduce two distinct ENUMERATIONS for the specification of potentially propagated and potentially controlled features. In such a case, color and height have to be part of the definition of the ENUMERATION Control (they are specified as ENUMERATION literals of Control), whereas movement has to be specified as literal in the ENUMERATION Propagation. Otherwise the AGGREGATION'S irreflexivity at the instance level is violated. "The data suggest that intransitivities arise due to equivocations between different types of semantic relations" (Winston, Chaffin, and Herrmann 1987:417). For example, compare Lyons' well-known 'handle-door-house' example (Lyons 1977a: 313-314): If a house has a door and the door has a handle, does the house have a handle? The term stock was coined by Cruse (1986:167). The attachment relationship is only mentioned briefly in the literature (Cruse 1979,1986; Winston, Chaffin, and Herrmann 1987). Though a group of people, for example, can be the possessor of a single pos-

366

142.

143.

144. 145. 146. 147. 148.

149. 150. 151. 152.

Notes sessee, the POSSESSION is never 'shared' in the sense of being distributed among the members of group. The priorities of conflicting TRANSITIONS are based on their relative position in the STATE hierarchy. " By definition, a TRANSITION originating from a subSTATE has higher priority than a conflicting TRANSITION originating from any of its containing STATES" (2-169). In general, if 11 is a TRANSITION whose source STATE is si, and t2 has source s2, then, if si is a direct or transitively nested subSTATE of s2, tl has higher priority than t2 (cf. 2-169). A concurrent STATE is a STATE that can be held simultaneously with other (concurrent and mutually orthogonal) STATES contained in the same COMPOSITE STATE. Naturally, they have to belong to different regions. Durative STATES are interrupted by an incoming EVENT forcing the OBJECT to leave the STATE, continuous SIGNALS by interrupting the SIGNAL sending OBJECT, that is, the SIGNAL sending OBJECT is forced to leave its STATE. A complex TRANSITION is also called a concurrent TRANSITION in the UML (cf.3-147). Whenever a composite STATE with concurrent regions is entered, each one of its regions is also entered, either by default or explicitly. When exiting from a composite STATE with concurrent regions, each of its regions is exited. After that, the exit actions of the regions are executed. " In general, a compound TRANSITION is an unbroken chain of TRANSITIONS joined via join, junction, choice, or fork PSEUDOSTATES that define a path from a set of source STATES (possibly a singleton) to a set of target STATES (possibly a singleton)" (2-164). For self TRANSITIONS, the same STATE acts as both the source and the target set. A simple TRANSITION connecting two STATES is therefore a special common case of a compound TRANSITION (cf. 2-164). In general, the prominent participants are - following Van Valin and LaPolla's (1997) terminology - the actor and the undergoer, if present. UML patterns are collaboration templates that describe the structure of design patterns. Interested readers are referred to the specification of the UML, cf. OMG (2001:2-134, 3-118-3-122). Cf. the description of classifier roles in the UML specification (3-125-3-127). This applies primarily to particular cases of reflexivity where a PARTICIPANT OBJECT plays two roles at the same time (cf. Section 9.3. for an example). It is not assumed that a PARTICIPANT OBJECT plays one role after the other in an eventity. For example, in the case of a transient spatial positioning of a participant at a location (i.e., the participant reaches the location and leaves it again), languages seem to attribute only one role to the location. Consider for example fetch in its prototypical sense: the undergoer's initial location is the actor's goal in the actor's first subevential movement, but also the source of the returning movement. Nevertheless, in, e.g., German, this location is attributed the source role of the undergoer's movement as part of the actor's returning movement (consider Ich hole mir ein Bier aus dem Kühlschrank Til fetch me a beer from the fridge', also cf. /'// go (*to) and get a beer from the fridge). More

Notes

153.

154.

155.

156.

157. 158. 159.

160.

367

complex role configurations are presumably not comprised by an eventity, that is, in a conceptual unit. For instance, participants playing the semantic role instrument are never cited in the dynamic core but are nevertheless participants, which is in these cases indicated by the PARTICIPATE ASSOCIATION. On the other hand, relations between participants modeled in ASSOCIATION CLASSES are not participants. Thus, they are not associated by PARTICIPATE ASSOCIATIONS to the dynamic core. It is tempting to assign a SWIMLANE to every participant. But for lexical semantic applications of the UER this would seem to be going too far, in particular because it would result in large diagrams with a lot of redundant and counterintuitive information. Consider the following example: A prominent participant P is transferred from location A to location B. At least three SWIMLANES would be needed: one for P, and also one for each A and B. These SWIMLANES would hold the information that P changes from being at A to being at B (SWIMLANE for P), that A changes from holding P to not holding P (SWIMLANE for A), and that B changes from not holding P to holding P (SWIMLANE for B). Nevertheless, such an approach might make sense for applications (and extensions) of the UER to discourse representation. Following the UML specification, for the creation of TEMPLATES "conceptually any model element may be used (but not all may be useful)" (2-72). Besides CLASS TEMPLATES which are explicitly depicted in the UML, EVENTITY FRAME TEMPLATES are of particular relevance in the UER. The definition of the binding relationship is broader in the UER than in the UML, as in the UML binding implies that all TEMPLATE parameters are assigned actual values (cf. 2-25-2-26,2-73, and 3-54-3-55), i.e. the UML's binding is the same as the UER's total binding. This has some non-trivial implications for implementation efforts. The German EVENTITY FRAME names have been selected to show that the example reflects semantic relations between lexemes in German. Bound elements, where a parameter has been bound specified, are semantic refinements of bound elements where the respective parameter has been bound unspecified. Relations between unspecified and specified bound elements of the same parameter can be captured using GENERALIZATION relationships, which express this superordinate concept - subordinate concept relation. The SUBCORE STATE concept is an interim solution for the nesting of subeventities within eventities. In other words, the fusing of eventities has to be handled somehow. Although this primarily seems to be a task for compositional semantics, verbal semantics cannot do without it. Therefore, the SUBCORE STATE is introduced. However, mechanisms or algorithms fusing different eventities are not yet established in the UER. Not only is a fusing of the dynamic cores difficult - there are still problems in that, for example, substructuring may be lost because of the lack of a swiMLANE-crossing structuring device - but also the static peripheries of the eventities to be fused have to be accommodated. As we expect a solution of this not to be a minor point, it has been postponed. Since it

368

Notes

reaches into compositional semantics, whose modeling we consider a task for further research. 161. In this case, the TRANSITION string of the TRANSITION outgoing from the SUBCORE STATE neither includes an EVENT specification nor the STEREOTYPE «spontaneous». 162. Additional participants of the subeventity are not cited in the SUBCORE STATE'S participant list. Chapter 6. 163. The BLACK BOX concept is the only advanced concept that is not dealt with in the interpretational part. Although we consider it to be important for the modeling of possibility and non-determinism, a relatively brief treatment (as it would inescapably be in this investigation) would by far not do it justice. For the complexity which is inherent in risk, for example, cf. Zaefferer (2002b). 164. The notion participant in UER terms includes only those participants which are conceptualized with regard to the modeled eventity, but is not limited to arguments that are encoded in the surface realization. On the one hand, the lexical semantics modeling of buy does not include a source role (Fillmore's 'Seller'). On the other hand, it is of course possible to have participants which are not morphosyntactically represented in the realization ('shadow' arguments or 'cognate' objects) but comprised by the semantics of a represented verb (as, for example, in rain, cf. Section 6.13.). 165. For other approaches towards frames in knowledge representation research, also cf. Barsalou (1992); Helbig (2001:357-363); or Sowa (2000a: 150): "A frame is a package of propositions about some type or some instance of a type". A treatment of frame-based representation languages in knowledge representation can be found in Reichgelt (1991:143-171). There, frames are introduced in the following way: "They are descriptions of objects. The descriptions in a frame are called slots. A slot usually consists of two parts: A slot-name, which describes an attribute, and a slot-filler, which describes either a value for that attribute or a restriction on the range of possible values" (Reichgelt 1991:144-145). A technical definition of 'frame' in artificial intelligence has evolved to mean 'a fixed set of name slots whose values vary across applications' (Barsalou 1992:28). 166. ENUMERATIONS are primitive data types, cf. Note 100 on p. 362. Note that the term value is not restricted to usages in a numerical sense. 167. Conceivably, ENUMERATIONS might also be applied for the specification of TEMPLATE PARAMETERS.

168. ENUMERATION names usually start with uppercase letters, whereas the associated PROPERTY names are depicted with lowercase letters. For example, the PROPERTY dimension is of the ENUMERATION type Dimension. Of course, this style guideline applies to ENUMERATION type PROPERTIES, Boolean PROPERTIES are shown differently, cf. Section 4.1.3. 169. This hypothetical restriction is partly due to the assumption that the 'limit of four' property of visual perception cited by Ifrah is a general cogni-

Notes

170.

171.

172.

173.

174.

175. 176.

369

tive constraint, implying, "daß die menschliche Fähigkeit zur unmittelbaren Wahrnehmung von Zahlen bzw. von konkreten Quantitäten sehr selten über die Zahl Vier hinausgeht" (Ifrah 1991:173) [that the human ability of immediate perception of numbers or concrete quantities very rarely exceeds the number four]. For typological comparisons, it might nonetheless be reasonable to start off with a significantly larger number of values in order to be able to capture overlapping, but non-coincident ranges of the assumed maximally five values. Compare for example German laufen and rennen', both are translatable by English run, although one would not translate Wir liefen sehr gemächlich (literally 'we ran very leisurely') as run but probably as trot or jog. Thus, run comprises rennen and overlaps with laufen, but laufen also includes an even lower level of velocity which is not captured by run. Starting with a larger number of values and then reducing this to the necessary amount to grasp all overlappings and all distinctions enables appropriate translations. Note, however, that it is likely that native speakers of a single language will not fully agree in their judgements on such gradings and that the assumption of a number of values which is not motivated on cognitive grounds is a quite artificial construct. Cruse mentions as a general characteristic of 'natural' or folk taxonomies that they typically have no more than five levels. These are commonly labelled as 'unique beginner', 'life-form' (or 'kind'), 'generic', 'specific', and 'varietal'. He expects the limitation to a maximum of five levels to exhibit general linguistic and cognitive constraints (Cruse 1986:145). Most interestingly, he elaborates on the importance of the generic level in Cruse (1977), stating that the generic level represents the 'unmarked' or 'neutral level of specificity' (Cruse 1977:154-155). Cf. also Stede (2000). It is not possible to depict the unmarked value using the unspecified string (' '), as this would indicate that the velocity value is conceptualized as existing but not explicitly specified. Deictic or reference point components are an example of why typological results are important for the creation of a universally applicable ENUMERATION inventory, as the components/literals have to be independent of languagespecificity. For example, cf. the different 'deictic strategies' that are employed in different languages (Hill 1982). For further potential ENUMERATIONS, cf. Talmy (2003), including categories such as Number (comprising as elements one, two, several, and many, Talmy 2003:8). However, mass-count distinctions are distinctions in ontological categories and treated as such (cf. Figure 65 on p. 197). As the latter use of ATTRIBUTES is rather a peripheral one in the UER, no emphasis is put on it in the following considerations about ATTRIBUTES. Cf. also Section 6.5. Of course, ATTRIBUTES can apply to any CLASS and they also constitute QUALIFIERS, but the occurrences mentioned here are the ones that are prominent in the UER framework.

370

Notes

177. For the application of the UER to verbal semantics, selectional restrictions are specified and these filter participants. Nevertheless, in other applications, such as dialog systems, the contrary view can be taken (and thus a bidirectionality is established): if a participant turns up in a particular eventity, the ATTRIBUTE specifications within the EVENTITY FRAME allow conclusions about which semantic features hold for the participant. These features are to be unified with the old information that is already available about the participant. This works as long as no counterexpectations to old information arise and if no type adaption (a mechanism which is considered to be similar to Pustejovsky's 'type coercion') applies. In the case of counterexpectations, belief revision takes place. The type adaption mechanism has not been worked out in detail to date and is, because of this and because it plays a role in questions of compositionality, not presented in this investigation. 178. All role ATTRIBUTES that are listed in the PARTICIPANT CLASS specification (i.e., ATTRIBUTES with superseding values or new ATTRIBUTES) may also be placed in a sub-compartment marked by the STEREOTYPE «role» as first list element in order to distinguish role ATTRIBUTES from those characterizing the participant. 179. For an informal specification of these STEREOTYPES, cf. Section A. 1. The declaration of all STEREOTYPES as well as of the specification of all ENUMERATION types within the framework of the UER cannot be accomplished in this investigation. 180. Another quale has already found its place within the UER: the constitutive quale is expressed by MERONOMY. 181. In most cases it will probably not be possible to capture all characteristics of a CLASS (this essentially corresponds to the 'definition problem' in lexical semantics). Therefore, we apply Langer's proposal for the semantic representation of a lexeme to our CLASSES and start with the central characteristics (note that the specification of CLASSES is easily extensible in adding ATTRIBUTES and ASSOCIATIONS): "Es läßt sich aber - zumindest im Normalfall - nicht festlegen, wann die semantische Kodierung eines Lexems vollständig ist. Die Bedeutungskodierung sollte von daher mit möglichst zentralen Aspekten der Bedeutung beginnen und problemlos erweiterbar sein" (Langer 1996:24). [But it cannot be determined - at least in the normal case - when a semantic encoding of a lexeme is comprehensive. The semantic encoding should therefore start with aspects of meaning that are as central as possible and it should be extensible without any problems.] 182. We are aware that true categorization and decomposition of eventities in fact involves a bidirectional process, where the categories and the results of decompositional analyses stimulate each other. But to decompose, we have to make assumptions about the categories in order to have a basis to work from. Probably, these assumptions have to be adjusted from time to time in the process of making the UER framework work. 183. Indeed, not all features that apply to a category are listed. We will only list

Notes

184.

185.

186.

187.

188. 189.

190. 191.

371

some important distinctive features, thereby developing a list which might be complemented during the use of the participant ontology. For an overview of types of ontologies and a treatment of different approaches, cf. Stein (1999:45-67). In particular, ontologies differ in what they categorize, for which purpose they categorize and how they categorize: "Ontotogien unterscheiden sich also in ihrer Ausrichtung (was wird kategorisiert?), ihrer Funktionalität (für welche Anwendung wird kategorisiert?) und ihrer Struktur (wie wird kategorisiert?)" (Stein 1999:47). [Ontologies hence differ in their orientation (what is categorized?), in their functionality (for which application is categorized?) and their structure (how is categorized?).] Most of the ontological distinctions are taken from Zaefferer (2002a). In particular, he coined the term eventity, supplementing it with the term inventity. As we want to avoide the connotation of 'invention', we use the term ineventity instead of inventity. Cf. also Goddard's 'topic roles' of eventities such as the ones represented by know, say, and think (as proposed within the NSM approach, cf. Section 2.3. or Goddard 1998:335). We tend to assume that the degree of concreteness of an entity corresponds to the degree in which it can be considered to be spatio-temporally locatable. The endpoints of the presumed scale can be characterized as follows. At the one end are concrete entities which are, when located, located spatially and temporally Lyons' first-order entities fall into this category (cf. Lyons 1977b: 443). Purely abstract entities, including Lyons' third-order entities, i.e., entities that are not spatio-temporally locatable, can be found at the other end. In between lie those entities which, if they are assigned a background setting, are temporally but not necessarily spatially located. This category comprises Lyons' second-order entities. The picture is surely not as simple as presented here, therefore, consider the three possibilities as prominent markers in this continuum. This enables, in particular, the establishing of conditions (GUARDS) with respect to a participant's location in the UER. Properties of entities are represented by ATTRIBUTES, in contrast to states of entities being represented by STATES. The difference in conception is that properties are considered to remain inalienable during the modeled eventity whereas states are not. In other words, characteristics which are in focus (or change) are modeled using STATES, while (non-focused) characteristics that are stable within the modeled eventity are depicted by ATTRIBUTES. The explicit conceptualization of mere existence is considered to be a state and thus eventity. Note that there are several competing classifications of Aktionsarten and of eventities in general, including the one suggested in Chapter 8. Deciding on a classification for the participant ontology will therefore not be an easy task. Nonetheless, several tests for the identification of Aktionsarten have been established (adverbial modification, intensity-gradability, etc.), cf., e.g., Dowty (1979); Pustejovsky (1991b); and Wanner (1999).

372

Notes

192. We may have to attribute this link between volitionality and animacy to our world knowledge. For example, consider a robot in a science fiction story that (or who?) is an artificial intelligence capable of acting volitionally. We would expect that it is tempting to attribute animacy to this robot because of its ability to act volitionally. Nevertheless, a future society using such robots might, because it experiences a much fuzzier boundary between animates and inanimates, distinguish in a more fine-grained way between animates and inanimates and might therefore not consider the robot to be animate. 193. In the UER, features of relationships are in general depicted as features of relational constructs (cf., e.g., ASSOCIATION CLASS and AGGREGATION). Prima facie, this principle seems to be broken with semantic role specifications in the form of role-expressions and additional role ATTRIBUTES within PARTICIPANT CLASSES. However, PARTICIPANT CLASSES are in fact relational concepts. As discussed in Section 6.4., PARTICIPANT CLASSES are constructs filtering entities and selecting those entities that are potential participants in an eventity. In a sense, they are thus not only decompositional CLASSES, but also relational constructs between existing entities (recall that prior existence of instances is assumed) and the eventities in question. 194. A recipient goal, i.e., a goal with the role ATTRIBUTE isReceiving = true, typically co-occurs with an additional AGGREGATION relation to the undergoer (the entity that is being received). The specificity of this AGGREGATION may vary extensively. 195. Prominent participants are those participants that own a SWIMLANE and whose PARTICIPATE ASSOCIATION is marked by either of the STEREOTYPES «do» or «undergo». Prominence of participants is a relational notion and obtained by a comparison of the static semantic roles represented in the PARTICIPANT CLASS. This largely follows and in general corresponds to the notions of proto-agent and proto-patient in Dowty's (1991) terms or to actor and undergoer in Van Valin and LaPolla's (1997) terms. Cf. also Section 6.13. 196. The corresponding ASSOCIATION relationships between the instruments and the actors are marked by the STEREOTYPE «apply», cf. Section A. 1. 197. Our notion of effector slightly differs from that presented in Van Valin and LaPolla's list in Section 2.1.2.1.: an effector is a non-volitional instigator of some change. 198. Since we consider causation to be a primitive concept (cf. Section 6.10.), we accordingly consider the abstract role Instigator, the parent of Agent and Effector, to be primitive. 199. A similar instrument interpretation for A ball broke the vase (in rolling info it) can also be found in Talmy (1985:79, 1997:31). Also, Talmy cf. (2000a: 473). 200. Differences in morphological marking often hint at prototypical differences, where morphological categories are considered to generally reflect fundamental categories, or, following Talmy's (2000a: 22) view, closed-class forms are considered to encode the fundamental structuring properties of the conceptual system.

Notes

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201. ASSOCIATION CLASSES are not only CLASSES, but also ASSOCIATIONS, so that the statements about ASSOCIATIONS apply to ASSOCIATION CLASSES as well. 202. Once again note that the inventories of PROPERTIES which can be propagated or controlled are not fixed at this stage and have to be developed gradually. 203. The notion "other attributes" refers to ATTRIBUTES in the UER. Meronomy as expressed by MERONOMY and semantic features as expressed by ATTRIBUTES are not both "attributes": although on a conceptual level one may consider an entity to have particular semantic features, these features are not conceptualized as parts and therefore as separate primary entities. Instead, they are characteristics and thus are represented via data types (that in general do not have an identity) such as Boolean type and ENUMERATION in the UER. Cf. also Helbig, who speaks about a 'dialectical unit' of entities and their features, where the features are attributed only a secondary status (Helbig 2001:57). 204. Cf., for example, Pustejovsky, who includes lexical inheritance structure into his Generative Lexicon, but does not supply a representational construct for it. In the UER, this is covered by GENERALIZATION. 205. Transient 'states', the PSEUDOSTATES, are not states and accordingly not represented as such. 206. Generally, durative adverbiale modify durative concepts such as states, activities, gradual transitions, and continuous causing. Thus, an appropriate UER representation (most probably using CONSTRAINTS) concerns PSSs, activity ASSs, gradual TRANSITIONS, and continuous SIGNALS. However, if non-durative acts are modified, the only interpretation allowing durativity is achieved in conceptualizing the non-durative acts as being repeated over and over again. This yields a durative repetitive eventity which is marked by the STEREOTYPE «repetitive» (cf. also Section 6.13.). 207. However, some features seem to be 'more intrinsic' than others: animacy is probably a feature that is conceived to be absolutely intrinsic (in that it cannot be changed at all according to contemporary world knowledge). Animacy as a feature does not even change if an entity comes into existence or ceases to exist (those cases are modeled using the create and destroy PSEUDOSTATES): we still attribute the semantic feature 'animate' to a dead person. Being female, on the other hand, is probably not as intrinsic as animacy (since transgenders exist). This is why we noted in Section 6.3. that the distinction between intrinsic and extrinsic might need further refinement, depending on the respective modeling purpose and the modeling granularity. 208. The proximity to implementation has been given up in favor of the proximity to conceptualization and a gain of intuitivity, but can be restored easily. 209. The same is true for SIGNALS, as continuous SIGNALS represent durativity. Cf. Section 6.10. 210. The metamodel inheritance structure, i.e., the inheritance structure of the UER's concepts, is particularly important for the specification of TEMPLATE parameter types (cf. Sections 5.5.1. and 6.12.). For the UML's metamodel, cf. the seman-

374

211.

212.

213. 214.

215.

216.

217.

218.

Notes tics chapter of OMG (2001). The explicit specification of the UER's metamodel will follow the UML's metamodel to some extent, but since there are many adapted and new concepts in the UER, the explication of the UER's metamodel is a task for future work. The access arrow (->) is used in one participant's SWIMLANE to reference another participant. This referenced participant's name is cited, followed by the access arrow and the specific background characteristic of the referenced participant, as in this case his location (also cf. the syntax for depicting pathnames in Section 5.2.1.). If no access arrow is used, this implies that the participant in whose SWIMLANE the condition is shown is concerned. In the given example, the condition of the change EVENT is true when the spatial locations of the two participants match. Elapsed-time EVENTS, i.e., those time EVENTS which are not change EVENTS, are not expected to occur very often, as verbs are assumed to only seldom include a fixed elapsation of time (such as 'after a month', 'after a day') in their semantics. Accomplishments, however, are represented using an activity ASS which is left when a condition - typically represented by a change EVENT - becomes true. The force dynamics Talmy (1988, 2000a, Chapter 7) proposes does not contradict the primitiveness of our notion of causation, as our notion merely entails the trigger itself. Although Talmy claims that force dynamics (which is not directed at lexical semantics) is "a generalization over the traditional linguistic notion of 'causative': it analyzes 'causing' into finer primitives" (2000a: 409), the factors he establishes do not interfere with the fact that causation involves a trigger (no matter whether, for example, the Agonist or the Antagonist is stronger, or whether their tendency is towards action or rest). Cf. the following pages, accessed on March 8, 2004: http://www.come2talk. de/webseiten/modules/newbb/viewtopic.php?topicjd=141&forum=9, http:// www.sgeintracht.de/html/einzelne.seiten/spruchjder_woche.htm, or http://forum.people.de/wbb2/thread.php?postid=3395. The last page also contains the neologisms wachzeigen 'to wake up by indicating' and wachvorführen 'to wake up by presenting', which are restricted in their interpretation to meaning extensions of wecken, i.e., which are exclusively hyponyms of 'making aware'. Interestingly, in many cases (if not all) the source STATE of such a TRANSITION seems to be modeled appropriately if displayed as unspecified. Accordingly, it is usually not parameterized. There is a polysemy in the latter two cases in whether the undergoer is hit (and destroyed) by the shot or is the 'ammunition' itself. We are currently dealing with the first reading. Such polysemies are not the focus and will be ignored for the moment, but they can be represented in the UER by developing different models for the readings. The prominent participants correspond roughly to the macroroles in the sense of Van Valin and LaPolla (1997), cf. Section 2.1.2.1. The difference lies in the purpose of tagging these participants: in Van Valin and LaPolla (1997), they

Notes

219.

220.

221.

222.

375

are marked in order to supply an appropriate linking, whereas in the UER they are those participants that are assigned SWIMLANES. Nevertheless, there is in principle strong agreement between the two notions. Moreover, the prominent participants correspond to the arguments of Jackendoff 's (1987, 1990) action tier (cf. Section 2.2.2.), where «do» corresponds to the first argument of the action tier, the affecting participant, and «undergo» to the second argument, the affected participant. For a detailed treatment on the concept of RAIN, its codings in English, German, Italian, and Spanish, and the linking mismatches which subsequently arise, cf. Zaefferer (2002a). Such linking mismatches can be captured within the UER using the default-property (cf. Section 6.14.), indicating that the corresponding participant is a default specification which may be overwritten in instantiation. The ENUMERATION OntoCat reflects ontological knowledge of language users, enumerating the different ontological categories with which language works. That is, the ontology on which natural languages are based comes into play (refining and supplementing the base references to the participant ontology in the PARTICIPANT TYPE specification). However, OntoCat as ENUMERATION type includes only the literals as a list and thus disregards systematical relations that exist between its ENUMERATION literals in cognition, such as water being a liquid. The Style ENUMERATION is not considered a fundamental cognitive category (cf. Section 6.2.), in the same way that most ENUMERATIONS in elements within the EVENTITY FRAME are. This is due to the fact that, in contrast to the latter, Style does not apply to the content of an EVENTITY FRAME, i.e., to the 'meaning in a narrow sense'. The other predefined CONSTRAINTS refer to relationships between model elements in order to indicate that, e.g., only one of several potential ASSOCIATIONS may be instantiated at a time (this is expressed by the xor-CONSTRAINT).

Chapter 7. 223. Moreover, the static periphery entails the characterization of the participants, their respective relations, and role specifications. 224. For a representation of TAKE and the static periphery of FETCH, cf. Figures 67 and 72. 225. For continuous SIGNALS, which have a duration, the sending and receipt are considered to occur simultaneously, i.e., both are continuous. 226. We do not take quick reaction times in psycholinguistic experiments as an indication of the primitiveness of tested elements. Rather, we believe that often encountered and employed clusters or chunks of elements are processed at a similar rate as often encountered and employed primitive elements - because of their permanent presence. Therefore, it is conceivable that particular carved out primitive elements might trigger a longer reaction time than particular chunks.

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Notes

227. However, the ENUMERATIONS themselves constitute fundamental cognitive categories, as for example Dimension or Velocity (cf. Section 6.2.). 228. The statal semantic primitives are considered to constitute a determined subset of the non-determined set of all STATES. Cf. also Section 7.3. 229. For example, it is not obvious whether mental states are primitive or not. 230. Spatial localizations are typically obtained by referencing non-abstract participants (and via these the background locations), because an absolute localizational grid is generally not used for spatial specifications (references to degrees of latitude or longitude could be seen as exceptional cases). Similar observations hold for temporal localizations, although the referenced participant is an abstract entity: temporal localizations are typically obtained by referring to cycles within the culture's own calendar system (cf., e.g., next week), and via these culture-specific relative time frames to the temporal background. 231. A PSS marked by «be-at» is comparable to queries of locations in change EVENTS, in that both inquire into the background against which eventides are evaluated. 232. As a complement to the locational keyword «be-at», the keyword «movealong» is introduced as reference to the spatio-temporal background - to indicate a movement along a path that is characterized by the participant referenced in the STATE'S name and the ASSOCIATION relation that holds between the participant in question and the referenced participant. 233. Another statal semantic primitive expressing conciousness might also be sensible, although this might be subsumed under the perception concept (note that Kalam expresses 'think' by gos /irj, literally 'mind perceive', cf. Pawleyl985:96). 234. It is not exceptional that fundamental elements of a single language's lexicon correspond to fundamental dynamic constructs of the UER. Another example is illustrated by the four bound markers of Walmajarri, which reflect part of the Aktionsart system, as they are bound up with activity and causation (for details, cf. Schalley 2003a). 235. We do not distinguish between those different types in our general treatment here, but subsume their semantics under the notion of compositional semantics, because they are all composed expressions. We are, of course, aware that detailed semantic analyses of these types will differ from one another. 236. This, however, will lead us to question whether particular grammatical properties can be attributed particular semantic fusion mechanisms. But we consider this questions and others such as the linking problem to be issues that are best addressed once we have a concise semantic theory and description tool. This again demonstrates that our approach is a purely semantic one (differently to most of the approaches discussed in Section 2.2.) and that questions of encoding are considered a second step, which we are not dealing with in this investigation. 237. This can be demonstrated with the following passage: James sits on the sofa. He unfortunately lost an arm about a month ago. The dog bit off his right arm after

Notes

377

Julia had left him lying on the floor in her room. She was very sorry about that; but because playing with him had not been so much fun any more, she put him on the sofa, where he has been sitting since. While the text is enfolding, our mental images are overwritten with each step, because more and more characteristics of the entity encoded by James and later referred to as he become available, so that our image of James becomes more and more accurate. The belief revision that takes place poses no problem to humans, however, because no contradiction to explicitly given information arises. Even though the prototypical effect will let most people picture a male human sitting on a sofa at the beginning, this is revised with more information becoming available. The semantics of sit (as displayed in Figure 60) easily allows for the interpretation that crystallizes in the course of the passage, because the doll James is an ineventity that just has to have the disposition of being locatable at a location in a sitting posture. 238. Modeling of instances naturally includes all the information that is available about the respective instances. 239. A time specification in terms of a time EVENT such as when(time = 3pm) is not possible, because that would imply that reaching 3pm was the trigger of the TRANSITION, and not that at 3pm is just additional information. Chapter 8. 240. Accordingly, general actions have never been considered as Aktionsart in their own right. 241. It should be noted that what is represented by activity ASSs and SIMPLE STATES in general in the UER only captures eventities that do not involve a second prominent participant. Eventities with two prominent participants are discussed in more detail in Section 8.3. In their modelings, the dynamic core comprises another SWIMLANE and the two prominent participants' interaction, i.e., some cause-siGNAL. 242. Modelings of repetitve acts in the UER comprise the act ASS supplemented by the STEREOTYPE «repetitive:», as has been discussed in Section 6.13. 243. There are more than 800 examples of loschatten in the Internet, amongst them, for example, http://www.bnv-gz.de/unterhaltung/einfuehrung.shtml and http://www.deutscherindex.de/Kontakte/Chat/morelO.html (accessed on December 18,2003). 244. Cf. http://www.entecker.ch/177.html and http://spotlight.de/zforen/std/rn/std1065775015-23161.html, accessed on December 18, 2003. 245. We do not use the term in its medical sense (as a gradual changing or tending to change of a morbid state into one of health), although the gradual changing into a state, i.e., the idea of alteration, is of course our motivation for this terminology. 246. I would like to thank to Dietmar Zaefferer for pointing me at the examples INFLATE, START-ROLLING, FALLJSILENT, DEFLATE, and ROLL_TO_A. STOP. 247. General causation as displayed here is different from the CAUSE-eventity that

378

248.

249.

250. 251.

252. 253.

254. 255.

Notes was discussed in Section 6.10., modeled in Figure 70, and instantiated in Example (5b). It might be sensible to assume that in principle both ASS and PSS are valid SIMPLE STATES for the actor, as PSSs representing the existence or localization of the actor participant may cause some change of state in the undergoer. But since SlGNAL-sending PSSs will be restricted to some particular cases and because general conceptualization indicates some action that triggers the change, we display an ASS as default in the following representations. In some cases of change eventities, such as ARRIVE, it seems to be difficult to conceptualize a corresponding causative interactional eventity, a fact that might be attributed to our world knowledge. However, there are differences in the grammatical behavior of the two hängen variants, cf. Section 9.1.1. The receipt of the cause-SIGNAL triggers the exit from the unspecified source STATE and hence the gradual TRANSITION. Accordingly, the cause-SIGNAL is shown between the source STATE and the gradual PSEUDOSTATE. This must be so, because if it were displayed between the gradual PSEUDOSTATE and the target STATE, the gradual TRANSITION would be interrupted by the SIGNAL receipt (cf. also Section 5.2.1.). For example, Amanda knows that Jim loves Jill presupposes that the proposition Jim loves Jill is true. An unspecified binding of the parameter Z in Figure 91 results in the general causation shown in Figure 87, which is thus, in a sense, an underspecified factive. I am indebted to Anke Hagedorn, a native speaker of DOS, for making me aware of this. Yet, such differences play a role in the behavior of encoding verbs (for instance, with regard to adverbial modification). A classification intended to reflect such differences should be more fine-grained. This can easily be achieved by relying on the structural differences that are expressed by different modeling elements oftheUER.

Chapter 9. 256. For a contemporary typological investigation into these posture verbs, cf. Newman (2002). 257. I would like to thank the Institut für Deutsche Sprache (IDS) in Mannheim for the opportunity to search COSMAS I online. The Cosmas corpus comprises several sub-corpora, containing both written and spoken data. The types of text from which the examples are selected include fiction and non-fiction literature, newspaper and magazine articles, fairy tales, myths, radio recordings, and light novels. The following summary gives the sub-corpora used in this investigation and lists in brackets the texts of the respective subcorpora from which example sentences are taken:

Notes BZK

379

Bonner Newspaper Corpus (daily newspaper Die Welt, 1954, 1969, FRG) GOE Goethe-Corpus (Johann Wolfgang von Goethe: Campagne in Frankreich; based on the Hamburg Edition in 14 Vols., ed. Erich Trunz, München: Beck 1982) GR1 Grammar-Corpu s (fiction literature: Alfred Andersch: Die Kirschen der Freiheit, Hans Joachim Schädlich: Versuchte Nähe; light novels: Claudia Torwegge: Liebe hat ihre eigenen Gesetze, Yvonne Bolten: Komteß Silvia von Schönthal, R. F. Garner: Gannons Gold, Barbara Balden: Nur ein einfaches Mädchen, Anne de Groot: Dein Vater wird uns liebgewinnen) GRI Grimm-Corpus (fairy tales, German myths, children's myths, collected by Jacob and Wilhelm Grimm; examples are taken from the following texts: Romhild und Grimoald der Knabe; Die Wichtelmänner; Der Meisterdieb; Die sechs Schwäne; Adelgis; Allerleirauh; Märchen von einem, der auszog, das Fürchten zu lernen; Der Fuchs und die Katze; Die zwei Brüder; Das Lumpengesindel; Karl Ynach, Salvius Brabon und Frau Schwan; Der goldene Vogel; Taube zeigt einen Schatz; Aschenputtel; Des Remigs Reil vom Wasichenwald; Hermann von Treffurt; Die Müllerin; Eppela Gaila; Die eingefallene Brücke) MK1 Mannheim Corpus l (fiction literature: Heinrich Böll: Ansichten eines Clowns, Günter Grass: Die Blechtrommel, Erwin Strittmatter: Öle Bienkopp; memoirs: Theodor Heuss: Erinnerungen 1905-1933; (popular) scientific: Bild der Wissenschaft, Pörtner: Die Erben Roms; non-fiction literature: Grzimek: Serengeti darf nicht sterben) MK2 Mannheim Corpus 2 (light novels: Pegg, J.: Nacht des Jägers, [Author unknown:] G-man Jerry Cotton. Ein Teenager soll sterben) MLD Corpus of 'Lufthansa Bordbuch' (magazine, 1995) MMM Mannheimer Morgen (daily newspaper, 2000) PFE Pfeffer-Corpus (colloquial spoken language, radio recordings; FRG, GDR, Switzerland; beginning of the 1960s) WKD 'Wendekorpus'/East (daily newspaper Berliner Zeitung, GDR, 1989) One reference is not part of the COSMAS I Corpus: SZM Süddeutsche Zeitung Magazin (magazine of the daily newspaper Süddeutsche Zeitung, 2002)

380

Notes

258. It has been refrained from specifying the source STATE as the opposite of the target STATE on purpose. We do not believe in a binarity of statal conceptualization as presented in Pustejovsky (1991b), for example. What exactly does it mean for Mary to be in the source state -> dead (Mary) (Pustejovsky 1991b: 60) - is she alive, ill, healthy, asleep, or something else? Hence, the specification of the source STATE seems to be provided by the context, if at all, but is, however, not part of the semantic representation. 259. It might be tempting to attribute the PARTICIPANT TYPE Individual to the volitional actor, because our world knowledge tells us that volitionality can in our world only be found in animate individuals (i.e., humans or at best animals) or groups of these. Nevertheless, this knowledge is not part of the semantics and thus the semantic representation, because if in a science fiction (consider Star Trek, for instance) there was a substance able to act volitionally, such as a nebula, we would not hesitate to accept that it can put other ineventities - as long as it has movement (and thus locational) control over these ineventities (cf. the following discussion of the AGGREGATION relation in the main body of the text). 260. LOCALIZED indicates a localizational, passive state of the undergoer, and would thus be more appropriately termed BE-LOCALIZED. For the sake of brevity, we nonetheless simply term the eventity 'LOCALIZED'. 261. The participants' roles and thus PARTICIPANT ROLES of containing and referenced eventity may of course differ from one another, because the characterization of a participant's role depends on the described eventity. Such a case can be found in the PUT-EVENTITY FRAME, where the ineventity playing the goal role in PUT holds the ground role in LOCALIZED. 262. Contact is an ENUMERATION with just two values, namely yes and no. This ATTRIBUTE could in principle also be modeled as contact: Boolean, but as the name of an ATTRIBUTE does not carry any semantics, the ENUMERATION Contact is preferred in this context. Thereby, a distinguishable recurring cognitive category is established (cf. Section 6.2.), which would not be the case if we went for the undistinguishable Boolean type. 263. Although there seems to be no absolute localizational grid (cf. Note 230 on p. 376), because of the force of gravity an absolute distinction in vertical vs. horizontal is nevertheless enabled, as well as the conception of a supporting 'base' is present. "Verticality in space coincides with the trajectory of every physical object submitted to the action of the force of gravity. This is perhaps also at the origin of the preference that verticality enjoys in human perception[]. In contrast to the horizontal axis, the vertical (gravitational) axis is always interrupted at the point where it encounters ground level" (SerraBorneto 1996:467-468), i.e., the supporting base (cf. also SerraBorneto 1996:463). 264. We expect the ENUMERATION Posture to include the ENUMERATION literals sitting, standing, lying, and possibly crouching and hanging. 265. The choice of ATTRIBUTES is guided by the aim to cover exactly those entities that are potential participants of the represented eventity. In the case of SITZEN,

Notes

266.

267. 268.

269.

270.

271. 272.

381

this includes that the undergoing ineventity must have the disposition of taking a sitting posture, whereas in the case of KILL the undergoer is better described as animate, because generally animate entities can be killed, i.e., they can die. Nothing similar holds for SITZEN, as all humans but only some animals (e.g., dogs), and some inanimate ineventities (e.g., dolls) are capable to 'sit'. We will allow ourselves a short comment on the design of the SUBCORE STATE in order to explain why SUBCORE STATES only reference the participant relationships and the dynamic core of the called subeventity: these are the parts of the modeling which are connected to the course of events (relations are established and deestablished, the dynamic core reflects the course of events). A referencing of PARTICIPANT CLASSES as part of the SUBCORE STATE call would not be sensible, because PARTICIPANT CLASSES select potential participants and therefore include preconditions for the whole eventity. These preconditions have to be met in order for a potential participant to be able to take part. That is, a participant taking part in an eventity that comprises a subeventity has of course to fulfill the selectional restrictions of the subeventity (the selectional restrictions of the subeventity constitute a subset of the selectional restrictions of the eventity). Hence, all selectional restrictions, of both containing and referenced eventity, have to be specified in the PARTICIPANT CLASSES of the containing eventity and, consequently, the PARTICIPANT CLASSES of the subeventity are not referenced by a SUBCORE STATE. Note that the two ATTRIBUTE adjustments correspond to the difference between the LOCALIZED and the SITZEN eventities. Accordingly, a distinction is not only not necessary for our investigational domain, but also not sensible and not enforced, as it is done in Schindler (2001) for the case of legen. This is done although in some cases another translation would suggest itself. The realization gesetzt in Example (5c), for example, would be more appropriately translated by seated. Although Anna setzte das Kind auf die Bank und sich daneben 'Anna put the child onto the bench and sat down next to it' is fine, this is not a counterexample, since two different eventity instances are described and connected by the junctor und 'and'. This becomes in particular clear when we explicate the goal participants which happen to be different: in the child's case the goal is the bench, whereas in Anna's case it is the child. For a discussion of the fact that the specification of the location may be omitted in the case of SICH_SETZEN, cf. below. A different conception is in her opinion not acceptable, "weil lokalen Verben damit ein unsystematisches Verhalten gerade im Zusammenhang mit dem lokalen Argument unterstellt wird, also dem Charakteristikum, das sie gegenüber anderen Verbklassen auszeichnet" (Maienbom 1991:97) [since unsystematic behavior is thereby imputed to verbs of position specifically in the context of the locational argument, that is, in that characteristic which distinguishes them from other verb classes].

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Notes

273. Both examples express physical control and thus caused movement. It is our feeling that the child can be put somewhere in a sitting posture more easily, whereas the thief making a corpse sit on his shoulders seems to be less likely, possibly primarily because of the corpse's size. 274. In (25a), undergoer and goal ineventity (i.e., the participant in reference to which the goal location is specified) are both elements of the same ontological category: both are feet - and both are parts of the actor. 275. Other PROPERTIES depend on the specific body part and are thus disregarded. For example, a meronomical relation between the agent (as determiner) and its head (as tolerator) entails the PROPERTY {mandatory}, because if the head is removed, the whole is destroyed. 276. For the prototypical readings, this is only possible for the reflexive variant, as discussed in Section 9.3.2. Evidence could at least only be found for SICH.SETZEN in the example corpus. 277. For the corresponding tests with a specified locational ineventity, add for instance auf dem Boden On the floor' to each sentence. Although the translations appear mostly clumsy because constructions corresponding to the German ones do not exist in English (compare sich setzen vs. its translation settle which forces us to add the ungrammatical reflexive pronoun in the English translations), we hope they nevertheless convey the basic idea. 278. I would like to thank Dietmar Zaefferer for pointing out the semantic change of sprengen and its potential relevance for my investigation to me. 279. As it is difficult to identify a plausible intermedium stage in the process of change, it is refrained from explicitly modeling such a stage. Yet, each stage could be modeled in the UER (modeling aspects are indicated in the text), but would probably be unstable, just like chemical compounds involved in a change do. 280. Correspondingly, in an encoding the constituent realizing the theme on the surface (i.e., the direct object) vanishes, and we are dealing with a typical unergative verb. 281. Hence, no constituent has to be encoded on the surface for the instrument. 282. Since abstract entities are not capable of taking a sitting posture and an undergoer taking a sitting posture can only do so in the concrete space, abstract entities are most likely not potential undergoers and goals of SETZEN, but presumably of PUT. Appendix A. 283. It is tempting to specify that they will always be placed on a given side of the line, but this is sometimes overridden by the need for clarity in a crowded diagram.

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