Improving name tagging by reference resolution and relation detection

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

Abstract

Information extraction systems incorporate multiple stages of linguistic analysis. Although errors are typically compounded from stage to stage, it is possible to reduce the errors in one stage by harnessing the results of the other stages. We demonstrate this by using the results of coreference analysis and relation extraction to reduce the errors produced by a Chinese name tagger. We use an N-best approach to generate multiple hypotheses and have them re-ranked by subsequent stages of processing. We obtained thereby a reduction of 24% in spurious and incorrect name tags, and a reduction of 14% in missed tags.

Original languageEnglish (US)
Title of host publicationACL-05 - 43rd Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference
PublisherAssociation for Computational Linguistics (ACL)
Pages411-418
Number of pages8
ISBN (Print)1932432515, 9781932432510
DOIs
StatePublished - 2005
Event43rd Annual Meeting of the Association for Computational Linguistics, ACL-05 - Ann Arbor, MI, United States
Duration: Jun 25 2005Jun 30 2005

Publication series

NameACL-05 - 43rd Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference

Other

Other43rd Annual Meeting of the Association for Computational Linguistics, ACL-05
CountryUnited States
CityAnn Arbor, MI
Period6/25/056/30/05

ASJC Scopus subject areas

  • Language and Linguistics
  • Linguistics and Language

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