Using corpus statistics and WordNet relations for sense identification

Authors:
Claudia Leacock;George A. Miller;Martin Chodorow
Affiliations:
Educational Testing Service;Princeton University;Hunter College of CUNY
Venue:
Computational Linguistics - Special issue on word sense disambiguation
Year:
1998

Citing 13
Cited 108

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Abstract

Corpus-based approaches to word sense identification have flexibility and generality but suffer from a knowledge acquisition bottleneck. We show how knowledge-based techniques can be used to open the bottleneck by automatically locating training corpora. We describe a statistical classifier that combines topical context with local cues to identify a word sense. The classifier is used to disambiguate a noun, a verb, and an adjective. A knowledge base in the form of WordNet's lexical relations is used to automatically locate training examples in a general text corpus. Test results are compared with those from manually tagged training examples.