EuroWordNet: a multilingual database with lexical semantic networks
EuroWordNet: a multilingual database with lexical semantic networks
Corelex: systematic polysemy and underspecification
Corelex: systematic polysemy and underspecification
Natural Language Engineering
Reducing lexical semantic complexity with systematic polysemous classes and underspecification
NAACL-ANLP-SSCNLPS '00 Proceedings of the 2000 NAACL-ANLP Workshop on Syntactic and semantic complexity in natural language processing systems - Volume 1
Tree-cut and a lexicon based on systematic polysemy
NAACL '01 Proceedings of the second meeting of the North American Chapter of the Association for Computational Linguistics on Language technologies
Polysemy and sense proximity in the Senseval-2 test suite
WSD '02 Proceedings of the ACL-02 workshop on Word sense disambiguation: recent successes and future directions - Volume 8
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We examine three different types of sense clustering criteria with an Information Retrieval application in mind: methods based on the wordnet structure (such as generalization, cousins, sisters...); co-occurrence of senses obtained from Semcor; and equivalent translations of senses in other languages via the EuroWordNet InterLingual Index (ILI). We conclude that a) different NLP applications demand not only different sense granularities but different (possibly overlapped) sense clusterings. b) co-occurrence of senses in Semcor provide strong evidence for Information Retrieval clusters, unlike methods based on wordnet structure and systematic polysemy. c) parallel polysemy in three or more languages via the ILI, besides providing sense clusters for MT and CLIR, is strongly correlated with co-occurring senses in Semcor, and thus can be useful for Information Retrieval as well.