A Wordnet from the Ground Up

Index 217mutual hypernymy, 24Mutual Information, 74, 80, 90Naïve Bayes, 131, 138Named Entity, 111Natural Language Processing, 7, 10, 11,13–15, 19, 47near-antonymy, 10near-synonym, 9, 10, 20, 42, 50, 94, 132–134, 148near-synonymy, 53, 92, 148negative semantic information, 71new lemma, 77, 145, 148–150, 152–155,159, 162, 163, 165–170, 179, 180,182NLP, see Natural Language Processingnominal lexical unit, 27, 30, 54, 56, 61,64, 68–72, 77, 78, 104, 107, 108,121, 130, 133, 135, 137, 170,180non-singleton synset, 178nounco-ordination, 64, 67, 131, 137phrase, 64, 66, 71, 101, 102, 104,108, 116, 135nouns, 9, 17, 21, 31, 34, 36, 52, 56, 60, 64,66, 67, 69, 72, 75, 108, 131, 133,136–137, 144, 147, 154, 155, 165,166, 170, 175object similarity, 64one-sense-per-discourse heuristic, 88ontological relation, 11ontology, 10, 11, 13Open Question Answering, 12parser, 64, 66part of speech, 8, 9, 35, 36, 45, 46, 175part-of-speech tagger, 112, 113partitioning clustering, 92patternconfidence, 115reliability, 114–116pattern confidence, 111pattern-basedapproach, 18, 48–50, 101, 102, 108,144, 166, 180extraction, 48Periscope, 38pertainymy, 10, 26, 32, 33, 46, 175, 190plWordNet, 10, 14–16, 18, 19, 21, 24–29, 31, 35–38, 42–46, 48, 50,51, 53–62, 64, 66, 70, 77–80,87, 90–92, 96, 97, 100, 102, 103,105, 106, 120–123, 126, 127, 130,137–142, 144, 153–157, 159, 163,165, 166, 170–172, 175–182plWordNetApp, 38–40, 42, 44, 152, 154,168, 177Pointwise Mutual Information, 74, 92, 97,113–116Polaris, 38Poleng parser, 66Polish, 10, 15–21, 32, 33, 36, 52, 56, 65,66, 77, 78, 83, 88, 95, 97, 102,113, 115–119, 121–123, 127, 129,147, 157, 176, 177, 181, 182Polish-English dictionary, 77, 80, 154PolNet, 14polysemous lemma, 17, 18, 27, 45, 61, 88,92, 170, 171polysemy, 21, 45, 46, 88, 171, 174polysemy rate, 172Princeton WordNet, 7–16, 18–21, 23–39,45, 47, 51, 141, 144, 146, 164,170–172, 177, 182PropBank, 13pure corpus approach, 77querybroadening, 12expansion, 12