mySENSEVAL: Explaining WSD System Performance Using Target Word Features
Word sense disambiguation (WSD) is an unsolved problem in NLP. The field has produced a variety of methods but none of them potent enough to reach high, human-tagger accuracy in demanding NLP applications. Our contribution to WSD is mySENSEVAL, an error analyzer using SENSEVAL evaluation scores (in mySQL database) to find significant correlations between WSD system types and lexico-conceptual features (from WordNet and SUMO).
KeywordsTarget Word Word Sense Disambiguation Lexical Resource Feature Typology Evaluation Workshop
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