Language independent NER using a unified model of internal and contextual evidence

  • Authors:
  • Silviu Cucerzan;David Yarowsky

  • Affiliations:
  • Johns Hopkins University, Baltimore, MD;Johns Hopkins University, Baltimore, MD

  • Venue:
  • COLING-02 proceedings of the 6th conference on Natural language learning - Volume 20
  • Year:
  • 2002

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Abstract

This paper investigates the use of a language independent model for named entity recognition based on iterative learning in a co-training fashion, using word-internal and contextual information as independent evidence sources. Its bootstrapping process begins with only seed entities and seed contexts extracted from the provided annotated corpus. F-measure exceeds 77 in Spanish and 72 in Dutch.