Abstract / Description of output
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 interpretations. We identify lexical semantic information automatically 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 human intuitions: meanings that are found highly probable by the model are also rated as plausible by the subjects.
Original language | English |
---|---|
Title of host publication | Second Meeting of the North American Chapter of the Association for Computational Linguistics |
Publisher | Association for Computational Linguistics |
Pages | 63-70 |
Number of pages | 8 |
Publication status | Published - 2001 |
Event | The Second Meeting of the North American Chapter of the Association for Computational Linguistics (NAACL 2001) - Pittsburgh, PA, United States Duration: 2 Jun 2001 → 7 Jun 2001 |
Conference
Conference | The Second Meeting of the North American Chapter of the Association for Computational Linguistics (NAACL 2001) |
---|---|
Country/Territory | United States |
City | Pittsburgh, PA |
Period | 2/06/01 → 7/06/01 |