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Abstract

This paper describes and evaluates an improved and modified version of the PALAVRAS-NER parser, adapted for the HAREM joint evaluation task of Named Entity Recognition (NER) in February 2005. Apart from an extension to over 40 semantic categories, the system was changed from a lexeme-based to a token-based description, defining NER categories as functional and context-based rather than stable and lexematic. The Constraint Grammar rule body was changed accordingly, adding new rules and applying existing heuristic and disambiguation rules to contextual re-mapping of also lexically known material. In the joint evaluation, PALAVRAS-NER achieved the best overall results, achieving top ranks for both the identification, classification and morphology tasks.

Keywords

Name Entity Recognition Entity Recognition Word Class Syntactic Parser Category Match 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Eckhard Bick
    • 1
  1. 1.Institute of Language and CommunicationUniversity of Southern DenmarkDenmark

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