Computing word-pair antonymy
Saif M. Mohammad, Bonnie Jean Dorr, Graeme Hirst · 2008
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.