Supersense tagging of unknown nouns using semantic similarity

James R. Curran
2005 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics - ACL '05  
The limited coverage of lexical-semantic resources is a significant problem for NLP systems which can be alleviated by automatically classifying the unknown words. Supersense tagging assigns unknown nouns one of 26 broad semantic categories used by lexicographers to organise their manual insertion into WORDNET. Ciaramita and Johnson (2003) present a tagger which uses synonym set glosses as annotated training examples. We describe an unsupervised approach, based on vector-space similarity, which
more » ... does not require annotated examples but significantly outperforms their tagger. We also demonstrate the use of an extremely large shallow-parsed corpus for calculating vector-space semantic similarity.
doi:10.3115/1219840.1219844 dblp:conf/acl/Curran05 fatcat:on23dwal5ngtzdekyhptzjiiae