Semi-supervised relation extraction with large-scale word clustering

Ang Sun, Ralph Grishman, Satoshi Sekine

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

We present a simple semi-supervised relation extraction system with large-scale word clustering. We focus on systematically exploring the effectiveness of different cluster-based features. We also propose several statistical methods for selecting clusters at an appropriate level of granularity. When training on different sizes of data, our semi-supervised approach consistently outperformed a state-of-the-art supervised baseline system.

Original languageEnglish (US)
Title of host publicationACL-HLT 2011 - Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics
Subtitle of host publicationHuman Language Technologies
Pages521-529
Number of pages9
StatePublished - Dec 1 2011
Event49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, ACL-HLT 2011 - Portland, OR, United States
Duration: Jun 19 2011Jun 24 2011

Publication series

NameACL-HLT 2011 - Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies
Volume1

Other

Other49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, ACL-HLT 2011
CountryUnited States
CityPortland, OR
Period6/19/116/24/11

    Fingerprint

ASJC Scopus subject areas

  • Language and Linguistics
  • Linguistics and Language

Cite this

Sun, A., Grishman, R., & Sekine, S. (2011). Semi-supervised relation extraction with large-scale word clustering. In ACL-HLT 2011 - Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies (pp. 521-529). (ACL-HLT 2011 - Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies; Vol. 1).