Computing Word-Pair Antonymy

Saif Mohammad, Bonnie Dorr, and Graeme Hirst

In Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP-2008), October 2008, Waikiki, Hawaii.
ABSTRACT: Knowing the degree of antonymy between words has widespread applications in natural language processing. Manually-created lexicons have limited coverage and do not include most semantically contrasting word pairs. We present a new empirical measure of antonymy which combines corpus statistics with the structure of a published thesaurus. The approach is evaluated on a set of closest-opposite questions, obtaining a precision of over 80%. Along the way, we discuss what humans consider antonymous and how antonymy manifests itself in utterances.


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