Paper: A Method For Word Sense Disambiguation Of Unrestricted Text

ACL ID P99-1020
Title A Method For Word Sense Disambiguation Of Unrestricted Text
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 1999
Authors

Selecting the most appropriate sense for an am- biguous word in a sentence is a central prob- lem in Natural Language Processing. In this paper, we present a method that attempts to disambiguate all the nouns, verbs, adverbs and adjectives in a text, using the senses pro- vided in WordNet. The senses are ranked us- ing two sources of information: (1) the Inter- net for gathering statistics for word-word co- occurrences and (2)WordNet for measuring the semantic density for a pair of words. We report an average accuracy of 80% for the first ranked sense, and 91% for the first two ranked senses. Extensions of this method for larger windows of more than two words are considered.