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The multilingual named entity recognition framework

Published:12 April 2003Publication History

ABSTRACT

This paper presents a multilingual system designed to recognize named entities in a wide variety of languages (currently more than 12 languages are concerned). The system includes original strategies to deal with a wide variety of encoding character sets, analysis strategies and algorithms to process these languages.

References

  1. Appelt D. and Israel D. (1999). Introduction to Information Extraction Technology. (IJCAI-99) Tutorial, Stockholm, Sweden (available at: http://www.ai.sri. com/~appelt/ie-tutorial/)Google ScholarGoogle Scholar
  2. Asahara M., Matsumoto M. (2000) Extended Models and Tools for High-performance Part-of-Speech Tagger". In Proceedings of Coling'2000, Saarbrücken, Germany, pp. 21--27. Google ScholarGoogle ScholarDigital LibraryDigital Library
  3. Bechet F., Nasr A., Genet F. (2000) Tagging Unknown Proper Names Using Decision Trees. In Proceedings of the 38th ACL Conference, Hong-Kong, pp. 77--84 Google ScholarGoogle ScholarDigital LibraryDigital Library
  4. Bikel D., Miller S., Schwartz R. and Weischedel R. (1997) Nymble: a high performance learning name-finder. In Proceeding of the 5th ANLP Conference, Washington, USA. Google ScholarGoogle ScholarDigital LibraryDigital Library
  5. Borthwick A. (1999) A maximum entropy approach for named entity recognition. PhD Thesis, New York University. Google ScholarGoogle ScholarDigital LibraryDigital Library
  6. Collins M. and Singer Y. (1999) Unsupervised models for named entity classification. In Proceedings of EMNLP/WVLC, 1999, MA, pp. 189--196.Google ScholarGoogle Scholar
  7. Cucchiarelli A. and Velardi P. (1999) Adaptability of linguistic resources to new domains: an experiment with proper noun dictionaries. In Proceedings of the Vextal Conference, Venice, Italy, pp. 25--30.Google ScholarGoogle Scholar
  8. Mikheev A., Moens M. and Grover C. (1999) Named Entity recognition without gazetteers. In Proceedings of the Annual Meeting of the European Association for Computational Linguistics EACL '99, Bergen, Norway, pp. 1--8. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Mooney R. (1993) Induction over the unexplained: using overly general domain theories to aid concept learning, Machine Learning, 10:79. Google ScholarGoogle ScholarDigital LibraryDigital Library
  10. MUC-6 (1995) Proceedings of the Sixth Message Understanding Conference (DARPA), Morgan Kaufmann Publishers, San Francisco.Google ScholarGoogle Scholar
  11. Poibeau T and Kosseim L. (2001) Proper-name Extraction from Non-Journalistic Texts. Proceeding of the 11th Conference Computational Linguistics in the Netherlands, Tilburg. Netherlands, Rodopi.Google ScholarGoogle Scholar
  12. Sekine S., Eriguchi Y. (2000) Japanese Named Entity Extraction Evaluation - Analysis of Results. In Proceedings of Coling'2000, Saarbrücken, Germany, pp. 1106--1110. Google ScholarGoogle ScholarDigital LibraryDigital Library
  13. Silberztein M. (1993) Dictionnaires électroniques. Masson, Paris.Google ScholarGoogle Scholar
  14. Yarowsky D. (1995) Unsupervised Word Sense Disambiguation rivaling Supervised Methods. In Proceedings of the 33rd ACL Conference, Cambridge, USA. Google ScholarGoogle ScholarDigital LibraryDigital Library
  1. The multilingual named entity recognition framework

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    • Published in

      cover image DL Hosted proceedings
      EACL '03: Proceedings of the tenth conference on European chapter of the Association for Computational Linguistics - Volume 2
      April 2003
      254 pages
      ISBN:1111567890

      Publisher

      Association for Computational Linguistics

      United States

      Publication History

      • Published: 12 April 2003

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      • Article

      Acceptance Rates

      Overall Acceptance Rate100of360submissions,28%

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