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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