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

Shachar Mirkin; Ido Dagan; Maayan Geffet

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

Shachar Mirkin, Ido Dagan, Maayan Geffet

Department of Computer Science

Research output: Contribution to conference › Paper › peer-review

37 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 language	English
Pages	579-586
Number of pages	8
State	Published - 2006
Event	21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics, COLING/ACL 2006 - Sydney, NSW, Australia Duration: 17 Jul 2006 → 21 Jul 2006

Conference

Conference	21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics, COLING/ACL 2006
Country/Territory	Australia
City	Sydney, NSW
Period	17/07/06 → 21/07/06

Bibliographical note

Publisher Copyright:
© 2006 Association for Computational Linguistics

Funding

We wish to thank Google for providing us with an extended quota for search queries, which made this research feasible.

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Cite this

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Integrating pattern-based and distributional similarity methods for lexical entailment acquisition. / Mirkin, Shachar; Dagan, Ido; Geffet, Maayan.
2006. 579-586 Paper presented at 21st International Conference on Computational Linguistics and 44th Annual Meeting of the Association for Computational Linguistics, COLING/ACL 2006, Sydney, NSW, Australia.

Research output: Contribution to conference › Paper › peer-review

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AU - Geffet, Maayan

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AB - 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.

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

Abstract

Conference

Bibliographical note

Funding

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