Preface ......................................................... 1
I FIRST PART: SETTING THE STAGE ................................ 5
1 Aims and Scope of This Book .................................. 7
1.1 Aims and Main Thesis .................................... 8
1.2 Reference in Practical Applications of Computing ....... 12
1.3 Computational Models of Reference Production ........... 14
1.4 Determining the Information Content of an re ........... 16
1.5 Focus on Speakers or Hearers? .......................... 18
1.6 Referring in One Shot .................................. 19
1.7 A Perspective on Reference: Information Sharing ........ 21
1.8 Summary of the Chapter ................................. 23
2 Theories of Reference ....................................... 25
2.1 What Makes a Referring Expression? ..................... 25
2.2 Knowing What Something Is .............................. 28
2.3 Denotation and Connotation ............................. 30
2.4 The Russell-Strawson Debate ............................ 32
2.5 Intensional Contexts ................................... 35
2.6 Attributive Descriptions and Misdescriptions ........... 37
2.7 Proper Names ........................................... 39
2.8 The Gricean Maxims and Relevance Theory ................ 41
2.9 Summary of the Chapter ................................. 43
3 The Psychology of Reference Production ...................... 45
3.1 Common Ground .......................................... 45
3.2 Audience Design and the Egocentricity Debate ........... 50
3.3 Rationality and the Gricean Maxims ..................... 55
3.4 Intrinsic Preference for Certain Attributes ............ 60
3.5 Comparing Preference with Discrimination ............... 63
3.6 Insights from Dialogue ................................. 66
3.7 Ecological Validity of Experiments ..................... 68
3.8 Summary of the Chapter ................................. 69
II SECOND PART: SOLVING THE CLASSIC REG PROBLEM ................ 71
4 Getting Computers to Refer .................................. 73
4.1 Computational Pre-history of reg ..................... 73
4.2 The California School .................................. 77
4.3 The Classic REG Task ................................... 80
4.4 Assumptions Behind the Classic REG Task ................ 83
4.5 Exploring the Gricean Angle Computationally ............ 86
4.6 The Incremental Algorithm .............................. 90
4.7 Logical (In)completeness ............................... 94
4.8 Computational Tractability of REG Algorithms ........... 97
4.9 Salience ............................................... 99
4.10 Summary of the Chapter ................................ 102
5 Testing REG Algorithms: The tuna Experiment ................ 105
5.1 Why the tuna Experiment? .............................. 107
5.2 How to Test a REG Algorithm? .......................... 109
5.3 The tuna Corpus and Its Annotation .................... 111
5.4 Analysis of the Furniture Corpus ...................... 117
5.5 Analysis of the People ├С├оrpus ......................... 120
5.6 Modelling a Plurality of Speakers ..................... 122
5.7 Lessons from the tuna Experiment ...................... 124
5.8 Lessons from the tuna Evaluation Challenges ........... 125
5.9 A Note on Alternative Metrics ......................... 127
5.10 Summary of the Chapter ................................ 128
6 Probabilistic and Other Alternatives to the Classic REG
Algorithms ................................................. 129
6.1 Variations in Language Production ..................... 130
6.2 Bayesian Models of Reference .......................... 133
6.3 Probabilistic Referential Overspecification: the pro
Algorithm ............................................. 136
6.4 Constraint Satisfaction for REG ....................... 144
6.5 Krahmer et al.'s Cost-Based Approach .................. 149
6.6 Appelt's Heirs: Reference as Part of a Wider Problem .. 152
6.7 Suminary of the Chapter ............................... 156
III THIRD PART: GENERATING A WIDER CLASS OF RES .............. 159
7 First Extension: Using Proper Names ........................ 161
7.1 Why Have Proper Names Been Neglected in REG? .......... 162
7.2 Inco├┤orating Proper Names into REG .................... 163
7.3 Reifying Properties ................................... 166
7.4 Challenges for REG Posed by Proper Names .............. 167
7.5 Summary of the Chapter ................................ 169
8 Second Extension: Referring to Sets ........................ 171
8.1 Purely Conjunctive References to Sets ................. 171
8.2 Negation and Disjunction .............................. 175
8.3 Satellite Sets and Their Use in REG ................... 178
8.4 Generating Boolean Logical Forms Incrementally ........ 181
8.5 Optimization of Generated res ......................... 185
8.6 Issues Raised by the Algorithms Proposed .............. 186
8.7 Lexical Coherence in Conjoined res .................... 187
8.8 Avoiding Surface Ambiguities .......................... 192
8.9 Beyond Sets of Objects ................................ 197
8.10 Summary of the Chapter ................................ 198
9 Third Extension: Using Gradable Properties ................. 201
9.1 The Semantics of Vague Descriptions ................... 202
9.2 Pragmatic Constraints on What Can Be Said ............. 204
9.3 Empirical Grounding ................................... 205
9.4 Computational Generation of Vague Descriptions ........ 206
9.5 Puzzles for Incremental Content Determination ......... 212
9.6 A Case Study: Real-Worid Objects and Their Sizes ...... 214
9.7 Can We Ever Be Clear? Salience as a Gradable
Property .............................................. 220
9.8 Summary of the Chapter ................................ 222
10 Fourth Extension: Exploiting Modern Knowledge
Representation ............................................. 225
10.1 Knowledge Representation and REG ...................... 226
10.2 Description Logic: a Primer ........................... 228
10.3 Applying Description Logic to Familiar REG Problems ... 230
10.4 Exploiting the Full Power of dl ....................... 234
10.5 Using SROIQ+ to Generate Complex REs .................. 238
10.6 Rethinking REG: Using Shared Knowledge That Is Not
Atomic ................................................ 242
10.7 Why Study the Generation of Logically Complex res? .... 246
10.8 Summary of the Chapter ................................ 249
11 The Question of Referability ............................... 251
11.1 Revisiting the Logical Completeness of REG ............ 251
11.2 Limitations of SROIQ+ and the growl Algorithm ......... 257
11.3 Even More Expressive Algorithms? ...................... 259
11.4 Summary of the Chapter ................................ 260
IV FOURTH PART: GENERALIZING REFERENCE GENERATION ............. 261
12 First Challenge: Large Domains ............................. 263
13 Second Challenge: Breakdown of Common Knowledge ......... 273
14 Third Challenge: Approximate Reference .................. 281
15 Fourth Challenge: Going Beyond Identification ........... 285
Summary of Part IV: Complexities of Information Sharing .... 292
V EPILOGUE ................................................... 293
16 Epilogue ................................................... 295
16.1 REG Algorithms as Cognitive Models .................... 296
16.2 The Gricean Maxims and the Principle of Intrinsic
Preference ............................................ 300
16.3 Future Research: The Way Ahead ........................ 304
Frequently Occurring Terms and Abbreviations .................. 311
Bibliography .................................................. 313
Index ......................................................... 333
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