Chinese syntactic parsing based on extended GLR parsing algorithm with PCFG

  • Authors:
  • Yan Zhang;Bo Xu;Chengqing Zong

  • Affiliations:
  • National Laboratory of Pattern Recognition, Beijing, P. R. China;National Laboratory of Pattern Recognition, Beijing, P. R. China;National Laboratory of Pattern Recognition, Beijing, P. R. China

  • Venue:
  • COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 2
  • Year:
  • 2002

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Abstract

This paper presents an extended GLR parsing algorithm with grammar PCFG* that is based on Tomita's GLR parsing algorithm and extends it further. We also define a new grammar---PCFG* that is based on PCFG and assigns not only probability but also frequency associated with each rule. So our syntactic parsing system is implemented based on rule-based approach and statistics approach. Furthermore our experiments are executed in two fields: Chinese base noun phrase identification and full syntactic parsing. And the results of these two fields are compared from three ways. The experiments prove that the extended GLR parsing algorithm with PCFG* is an efficient parsing method and a straightforward way to combine statistical property with rules. The experiment results of these two fields are presented in this paper.