Computing Word-Pair Antonymy

نویسندگان

  • Saif Mohammad
  • Bonnie J. Dorr
  • Graeme Hirst
چکیده

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 automatic and empirical measure of antonymy that 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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تاریخ انتشار 2008