A step-wise usage-based method for inducing polysemy-aware verb classes

Daisuke Kawahara, Daniel W. Peterson, Martha Palmer

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

11 Citations (Scopus)

Abstract

We present an unsupervised method for inducing verb classes from verb uses in gigaword corpora. Our method consists of two clustering steps: verb-specific semantic frames are first induced by clustering verb uses in a corpus and then verb classes are induced by clustering these frames. By taking this step-wise approach, we can not only generate verb classes based on a massive amount of verb uses in a scalable manner, but also deal with verb polysemy, which is bypassed by most of the previous studies on verb clustering. In our experiments, we acquire semantic frames and verb classes from two giga-word corpora, the larger comprising 20 billion words. The effectiveness of our approach is verified through quantitative evaluations based on polysemy-aware gold-standard data.

Original languageEnglish
Title of host publicationLong Papers
PublisherAssociation for Computational Linguistics (ACL)
Pages1030-1040
Number of pages11
ISBN (Print)9781937284725
DOIs
Publication statusPublished - 2014
Externally publishedYes
Event52nd Annual Meeting of the Association for Computational Linguistics, ACL 2014 - Baltimore, MD, United States
Duration: 2014 Jun 222014 Jun 27

Publication series

Name52nd Annual Meeting of the Association for Computational Linguistics, ACL 2014 - Proceedings of the Conference
Volume1

Conference

Conference52nd Annual Meeting of the Association for Computational Linguistics, ACL 2014
Country/TerritoryUnited States
CityBaltimore, MD
Period14/6/2214/6/27

ASJC Scopus subject areas

  • Language and Linguistics
  • Linguistics and Language

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