Natural Language Processing
with ThoughtTreasure
TABLE OF CONTENTS
Preface xi
Chapter 1 Introduction 1
What does ThoughtTreasure do? 1
ThoughtTreasure and this book 4
Size comparison with other systems 6
The ThoughtTreasure paradigm 7
Chapter 2 The representation agency 11
Representation and the movie review application 11
Collecting data from a corpus 11
Adding media objects to the ontology 12
Adding relations and attributes to the ontology 14
A brief tour of the ontology 17
Humans 17
Relations 17
Enums 18
Actions 18
Physical objects 19
Related work 20
Objects 20
Atomic objects 20
Lists and assertions 21
Constants 24
Object routines 25
The representation of time 25
Timestamps 25
Timestamp ranges 26
Time of day 26
Duration 26
Extended timestamp ranges 27
Time routines 27
The representation of space 28
Grids 28
Wormholes 31
Finding paths within grids 32
Finding paths between grids through wormholes 33
Objects in space 33
Locating objects 33
Calculating the distance between objects 33
Finding enclosing objects 34
Nearness 34
Polities 35
The geography ontology 35
Calculating the distance between two polities 36
Polity routines 36
Database assertion and retrieval 36
Assertion 36
Retrieval 37
Retraction 38
Unification 38
Instantiation 39
Theorem proving 39
The intension resolver 40
Contexts 42
Contexts and database assertion/retrieval 43
Actors inside contexts 44
Discourse 44
Exercises 45
Chapter 3 The lexical component 47
The lexicon and the movie review application 47
Coding lexical entries 53
Coding words 53
Coding phrases 54
Coding verb argument structure 55
Intransitive verbs 55
Transitive verbs 56
Verbs with prepositional phrase arguments 56
Verbs with noun phrase and prepositional phrase arguments 58
Slot numbers 58
Verbs with clause arguments 59
Phrasal verbs 62
Pronominal and negative phrasal verbs 63
Coding lexical entries for gradable concepts 65
Coding relations and roles 66
Attribute-relation connections 68
Coding attachments 69
Coding isms 69
Parsing- and generation-only predicates 70
Wholes for parts: Metonymy coercion 70
Coding human names 71
Lexical tools 71
Lexical entry scanner 71
Inflection scanner 71
Polysemous lexical entry dumper 72
Ambiguous part-of-speech inflection dumper 72
Coverage checker 73
Concordance generator 74
Corpus-based adverbial finder 74
Corpus-based lexicon verifier 75
Exercises 75
Chapter 4 The text agency 81
The text agency and the movie review application 81
A tour of the text agency 84
Lexical entry text agent 88
Scanning lexical entries 88
Part-of-speech tagging 90
Name text agent 91
Representing names 92
Learning new names 93
Time text agent 94
Telephone number text agent 97
Media object text agent 98
Product text agent 98
Adding products to the database 99
Price text agent 100
End of sentence text agent 100
Communicon text agent 101
Email header text agent 101
Attribution text agent 103
French polity text agent 104
Exercises 104
Chapter 5 The syntactic component 105
The base component 105
Filters 107
X-bar filters 108
Adjective filters 111
Adverb filters 112
Conjunction filters 113
Noun filters 114
Relative pronoun filters 116
Verb filters 117
Other filters 118
The bottom-up syntactic parser 119
Transformations 120
English and French transformations 121
English transformations 122
French transformations 123
Exercises 123
Chapter 6 The semantic component 125
ThoughtTreasure's parsing control structure 126
Parsing and the movie review application 126
Parsing and answering a question 127
Parsing a movie review 135
The semantic parser 135
Case frames 136
Semantic Cartesian product 137
Parsing maximal projections 138
Adding arguments to the case frame 138
Theta marking 140
Noncopula theta marking 141
Parsing predicates 141
Parsing adjuncts 141
Parsing copulas 142
Parsing equative roles 143
Parsing ascriptive attachments 143
Parsing compound tenses 143
Parsing verbs 146
Parsing nouns 147
Parsing adjectives 148
Parsing adverbs 149
Parsing conjunctions 150
Parsing genitives 150
Parsing appositives 151
Parsing relative clauses 151
Parsing nominal relative clauses 152
Parsing nonnominal relative clauses 153
Parsing other parse nodes 154
The anaphoric parser 154
Antecedents 155
Resolving pronouns 156
Resolving third-person pronouns 157
Resolving deictic pronouns 158
Resolving articles and intensions 159
Resolving possessive determiners 161
Applying coreference constraints 161
Generating pronouns 162
Generating articles 163
Aspect 164
Aspect representation 164
Aspect in parsing 166
Aspect in generation 166
Generating adverbial clauses of time 166
Determining aspect and tense of simple sentences 171
The generator 171
Exercises 171
Chapter 7 The planning agency 175
An example simulation 175
Planning agents 176
Grasper planning agents and containers 177
Small containers 179
Large containers 180
Example: Moving a penny from one jar to another 181
Trips 183
Finding trips 185
Finding grid-wormhole traversal trips 186
Finding driving trips 186
Finding scheduled trips 187
Ptrans planning agents 187
Atrans planning agents 190
Mtrans planning agents 193
Telephone planning agent 194
Entertainment planning agents 197
Clothing 197
Clothing planning agents 200
Shower planning agent 201
Sleep planning agent 204
Appointment planning agent 205
Maintain friendship planning agent 206
Planning agency control structure 206
Exercises 207
Chapter 8 The understanding agency 209
Understanding agents with common sense 210
Understanding agency control structure 213
B-Brain 214
Emotion understanding agent 214
Goal understanding agent 216
Friend understanding agent 216
Relation understanding agent 218
Question answering agents 220
Yes-No question answering agent 221
Question word question answering agent 221
Location adverb question answering agent 221
Location pronoun question answering agent 222
Nearby object question answering agent 222
Time adverb question answering agent 222
Duration question answering agent 222
Temporal relation question answering agent 222
Timestamp request question answering agent 223
Degree adverb question answering agent 223
Quantity question answering agent 223
Pronoun question answering agent 224
Top-level question element question answering agent 224
Weather question answering agent 224
Appointment question answering agent 224
Description question answering agent 225
Means adverb question answering agent 225
Reason adverb question answering agent 225
Explanation question answering agent 225
Dictionary agent 226
Understanding as simulation 230
The combination lock metaphor for understanding 232
Spinning a planning agent to a state 234
Example: Sleep and shower understanding agents 234
Time understanding agent 236
Space understanding agent 237
Weather understanding agent 237
Sleep understanding agent 237
Shower understanding agent 238
Example: Appointment, asker, and emotion understanding agents 238
Appointment understanding agent 239
Question asking agent 239
Trade understanding agent 243
Occupation understanding agent 244
Analogy understanding agent 244
Toward a story understanding program 246
Exercises 254
Chapter 9 Learning in ThoughtTreasure 257
Learning from tables in text 257
Sensing the presence of a table 258
Parsing the sensed table 260
Learning from the parsed table 261
Learning inflectional morphology 261
Algorithmic morphology 262
Analogical morphology 263
Training 263
Application 264
Induced morphological paradigms 264
Learning new words via derivational morphology 265
Derivational rules 266
Processing new words 267
Output of learning 268
Word formation tool 270
Learning derivational rules 270
ThoughtTreasure data mining 271
French gender rules 271
Standard and inverse alphabetical dictionaries 272
Phrasal derivation 273
Faux amis 274
Anagrams and palindromes 274
Exercises 275
Chapter 10 Applications of ThoughtTreasure 279
Chatterbot 279
Data extraction 285
How ThoughtTreasure parses a Usenet ad 286
Translation 286
Interlingual translation 286
Transfer-based translation 287
Associative thought stream generation 289
Ontologies for Internet context indexing 290
The ThoughtTreasure shell 292
Statistics on ThoughtTreasure lexical entries 292
Statistics on ThoughtTreasure objects 294
Chapter 11 Experiences and unexpected results 297
Unexpected question answers 297
Unexpected syntactic parses 300
Unexpected semantic parses 300
Unexpected spellings 301
Unexpected text agent parses 302
Unexpected generation output 302
Unexpected planning results 303
Chapter 12 Conclusions and future work 305
The evolution of a new cyberspatial intelligence 307
Exercises 309
Appendix A: ThoughtTreasure shell commands 311
Appendix B: ThoughtTreasure manual page 315
Appendix C: ThoughtTreasure feature characters 316
Appendix D: ThoughtTreasure database file format 319
Bibliography 321
Index 329
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