Chunking with maximum entropy models

  • Authors:
  • Rob Koeling

  • Affiliations:
  • SRI Cambridge

  • Venue:
  • ConLL '00 Proceedings of the 2nd workshop on Learning language in logic and the 4th conference on Computational natural language learning - Volume 7
  • Year:
  • 2000

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Abstract

In this paper I discuss a first attempt to create a text chunker using a Maximum Entropy model. The first experiments, implementing classifiers that tag every word in a sentence with a phrase-tag using very local lexical information, part-of-speech tags and phrase tags of surrounding words, give encouraging results.