Two statistical parsing models applied to the Chinese Treebank

  • Authors:
  • Daniel M. Bikel;David Chiang

  • Affiliations:
  • University of Pennsylvania, Philadelphia, PA;University of Pennsylvania, Philadelphia, PA

  • Venue:
  • CLPW '00 Proceedings of the second workshop on Chinese language processing: held in conjunction with the 38th Annual Meeting of the Association for Computational Linguistics - Volume 12
  • Year:
  • 2000

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Abstract

This paper presents the first-ever results of applying statistical parsing models to the newly-available Chinese Treebank. We have employed two models, one extracted and adapted from BBN's SIFT System (Miller et al., 1998) and a TAG-based parsing model, adapted from (Chiang, 2000). On sentences with ≤40 words, the former model performs at 69% precision, 75% recall, and the latter at 77% precision and 78% recall.