NER systems that suit user's preferences: Adjusting the recall-precision trade-off for entity extraction

Einat Minkov, Richard C. Wang, Anthony Tomasic, William W. Cohen

Research output: Contribution to conferencePaperpeer-review

Abstract

We describe a method based on “tweaking” an existing learned sequential classifier to change the recall-precision tradeoff, guided by a user-provided performance criterion. This method is evaluated on the task of recognizing personal names in email and newswire text, and proves to be both simple and effective.

Original languageEnglish
Pages93-96
Number of pages4
StatePublished - 2006
Externally publishedYes
Event2006 Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics, HLT-NAACL 2006 - New York, United States
Duration: 4 Jun 20069 Jun 2006

Conference

Conference2006 Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics, HLT-NAACL 2006
Country/TerritoryUnited States
CityNew York
Period4/06/069/06/06

Bibliographical note

Publisher Copyright:
© 2006 Association for Computational Linguistics

ASJC Scopus subject areas

  • Linguistics and Language
  • Language and Linguistics
  • Computer Science Applications

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