Integrating pattern-based and distributional similarity methods for lexical entailment acquisition

Shachar Mirkin, Ido Dagan, Maayan Geffet

Research output: Contribution to conferencePaperpeer-review

36 Scopus citations

Abstract

This paper addresses the problem of acquiring lexical semantic relationships, applied to the lexical entailment relation. Our main contribution is a novel conceptual integration between the two distinct acquisition paradigms for lexical relations - the pattern-based and the distributional similarity approaches. The integrated method exploits mutual complementary information of the two approaches to obtain candidate relations and informative characterizing features. Then, a small size training set is used to construct a more accurate supervised classifier, showing significant increase in both recall and precision over the original approaches.

Original languageEnglish
Pages579-586
Number of pages8
StatePublished - 2006
Event21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics, COLING/ACL 2006 - Sydney, NSW, Australia
Duration: 17 Jul 200621 Jul 2006

Conference

Conference21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics, COLING/ACL 2006
Country/TerritoryAustralia
CitySydney, NSW
Period17/07/0621/07/06

Bibliographical note

Publisher Copyright:
© 2006 Association for Computational Linguistics

Fingerprint

Dive into the research topics of 'Integrating pattern-based and distributional similarity methods for lexical entailment acquisition'. Together they form a unique fingerprint.

Cite this