Paper: A Corpus-Based Account Of Regular Polysemy: The Case Of Context-Sensitive Adjectives

ACL ID N01-1009
Title A Corpus-Based Account Of Regular Polysemy: The Case Of Context-Sensitive Adjectives
Venue Annual Conference of the North American Chapter of the Association for Computational Linguistics
Session Main Conference
Year 2001
Authors

In this paper we investigate polysemous adjectives whose meaning varies depending on the nouns they modify (e.g. , fast). We acquire the meanings of these adjectives from a large corpus and propose a probabilistic model which provides a ranking on the set of possible interpre- tations. We identify lexical semantic information auto- matically by exploiting the consistent correspondences between surface syntactic cues and lexical meaning. We evaluate our results against paraphrase judgments elicited experimentally from humans and show that the model’s ranking of meanings correlates reliably with hu- man intuitions: meanings that are found highly probable by the model are also rated as plausible by the subjects.