Named Entity recognition without gazetteers

  • Authors:
  • Andrei Mikheev;Marc Moens;Claire Grover

  • Affiliations:
  • University of Edinburgh, Edinburgh, UK;University of Edinburgh, Edinburgh, UK;University of Edinburgh, Edinburgh, UK

  • Venue:
  • EACL '99 Proceedings of the ninth conference on European chapter of the Association for Computational Linguistics
  • Year:
  • 1999

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Abstract

It is often claimed that Named Entity recognition systems need extensive gazetteers---lists of names of people, organisations, locations, and other named entities. Indeed, the compilation of such gazetteers is sometimes mentioned as a bottleneck in the design of Named Entity recognition systems.We report on a Named Entity recognition system which combines rule-based grammars with statistical (maximum entropy) models. We report on the system's performance with gazetteers of different types and different sizes, using test material from the MUC-7 competition. We show that, for the text type and task of this competition, it is sufficient to use relatively small gazetteers of well-known names, rather than large gazetteers of low-frequency names. We conclude with observations about the domain independence of the competition and of our experiments.