Enriching entity translation discovery using selective temporality

Gae Won You, Young Rok Cha, Jinhan Kim, Seung Won Hwang

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

5 Citations (Scopus)

Abstract

This paper studies named entity translation and proposes "selective temporality" as a new feature, as using temporal features may be harmful for translating "atemporal" entities. Our key contribution is building an automatic classifier to distinguish temporal and atemporal entities then align them in separate procedures to boost translation accuracy by 6.1%.

Original languageEnglish
Title of host publicationShort Papers
PublisherAssociation for Computational Linguistics (ACL)
Pages201-205
Number of pages5
ISBN (Print)9781937284510
Publication statusPublished - 2013 Jan 1
Event51st Annual Meeting of the Association for Computational Linguistics, ACL 2013 - Sofia, Bulgaria
Duration: 2013 Aug 42013 Aug 9

Publication series

NameACL 2013 - 51st Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference
Volume2

Other

Other51st Annual Meeting of the Association for Computational Linguistics, ACL 2013
CountryBulgaria
CitySofia
Period13/8/413/8/9

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All Science Journal Classification (ASJC) codes

  • Language and Linguistics
  • Linguistics and Language

Cite this

You, G. W., Cha, Y. R., Kim, J., & Hwang, S. W. (2013). Enriching entity translation discovery using selective temporality. In Short Papers (pp. 201-205). (ACL 2013 - 51st Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference; Vol. 2). Association for Computational Linguistics (ACL).