A Wordnet from the Ground Up

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Index 219SUMO, 14Supported Vector Machines, 132, 141Swigra, 66synonym, 7, 20, 24, 28, 31, 35, 38, 52,58, 79, 84, 148synonymy, 8, 9, 11, 17, 21, 23–27, 52,149, 152, 160, 177, 178, 185test, 52, 92synset, 7–11, 13, 15, 17, 19–21, 23–46,53, 54, 57, 58, 77, 87, 96–97,130, 143, 144, 148–153, 155, 157,160, 163, 169–180, 182editing perspective, 42perspective, 39–42, 44probability, 51, 96properties, 40relation, 27, 40–42similarity, 96size, 54, 172syntacticdependency relation, 64relation, 64, 65, 135t-score measure, 74, 125, 134, 136TaKIPI, 66, 103, 157, 158target synset, 40, 42taxonomy, 11Test of English as a Foreign Language,52–53, 63TextSegmentation, 12Summarisation, 12text window, 63–65, 111, 134, 145Textual Entailment, 12The IPI PAN Corpus, 36<strong>the</strong>saurus, 7, 8, 15, 19, 50TOEFL, see Test of English as a ForeignLanguagetoken, 36, 37, 67, 68, 77, 103, 112, 121,154, 176transformation, 73, 74troponym, 28, 29troponymy, 9, 26, 28, 29, 46, 175, 188vector similarity measure, 74Vector Space Model, 88verb constraint, 83verbalhypernymy, 29lemmas, 80lexical unit, 29, 54, 56, 70, 72, 85,170, 172, 173, 180, 182verbs, 9, 21, 28–29, 31–33, 37, 64, 67,70, 73, 80, 84, 85, 166, 170, 181,182VisDic, 38WBST, see WordNet-Based Synonymy TestWBST with Hypernyms, 53–61, 77–78,80, 98, 137WBST+H, see WBST with Hypernymsweak fit, 150–152, 157–158, 163, 164weighted voting, 149, 150weighting, 65, 73, 74, 76, 80Weka, 138Wikipedia, 131WNW, see WordNet Weaverword form, 8, 17, 24, 36, 41, 42, 45, 61,65, 66, 68, 78, 112, 116, 117,129, 158Word Sense Disambiguation, 11–12, 182Word Space, 63WordNet, see Princeton WordNetDomains, 13wordnet, 7–19, 21, 36–38, 45, 50, 51, 53,87, 143, 144, 148, 149, 151, 152,155, 163, 164, 171, 176–179, 181,182expansion, 16, 107, 126, 130, 134,143, 148, 154, 164, 175, 179translation, 19
220 Indexcritic, 48editor, 38, 42, 152, 168enrichment, 13expansion, 47, 48, 50, 53, 54, 57, 59,65, 77, 79, 87, 165–169model, 18, 182relation, 19, 38, 48, 52, 57, 77, 79–80, 87, 119, 131, 143, 147similarity function, see semantic similaritytranslation, 20, 36WordNet Weaver, 16–18, 42, 46, 79, 141,152, 154–159, 165–168, 177, 179–182WordNet-Based Synonymy Test, 52–61, 85z-score measure, 125
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A Wordnetfrom the Ground Up
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Work financed by the Polish Ministr
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6 Prefaceheartfelt thanks go to all
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8 Chapter 1. Motivation, Goals, Ear
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1.1. Motivation 11[a] special form
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1.1. Motivation 13Affect (Strappara
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1.2. The Goals of the plWordNet Pro
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1.2. The Goals of the plWordNet Pro
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1.3. Early Decisions 19Merge Model:
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1.3. Early Decisions 214. On the ot
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24 Chapter 2. Building a Wordnet Co
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48 Chapter 3. Discovering Semantic
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102 Chapter 4. Extracting Relation
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166 Chapter 5. Polish WordNet Today
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Page 186 and 187: Appendix ATests for Lexico-semantic
Page 188 and 189: 187Test for adjectives (T. IX)1. p1
Page 190 and 191: 189RelatednessTest for nouns (T. XV
Page 192 and 193: BibliographyAgarwal, Abhaya and Alo
Page 194 and 195: Bibliography 193on Deep Lexical Acq
Page 196 and 197: Bibliography 195Derwojedowa, Magdal
Page 198 and 199: Bibliography 197Grefenstette, Grego
Page 200 and 201: Bibliography 199Kurc, Roman. (2008)
Page 202 and 203: Bibliography 201Mohammad, Saif and
Page 204 and 205: Bibliography 203. (2006) “The pot
Page 206 and 207: Bibliography 205and Technology 7(1-
Page 208 and 209: List of Tables2.1 The size of the c
Page 210 and 211: List of Figures2.1 The LU perspecti
Page 212 and 213: List of Figures 2114.16 Completely
Page 214 and 215: Index 213CBC, see Clustering by Com
Page 216 and 217: Index 215169, 177, 178, 180, 182hyp
Page 218 and 219: Index 217mutual hypernymy, 24Mutual
Page 222: A language without a wordnet is at
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A Wordnet from the Ground Up

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