Fast Chinese syntactic parsing method based on conditional random fields

Lei Han, Sen Lin Luo, Qian Rou Chen, Li Min Pan*

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

A fast method for phrase structure grammar analysis is proposed based on conditional random fields (CRF). The method trains several CRF classifiers for recognizing the phrase nodes at different levels, and uses the bottom-up to connect the recognized phrase nodes to construct the syntactic tree. On the basis of Beijing forest studio Chinese tagged corpus, two experiments are designed to select the training parameters and verify the validity of the method. The result shows that the method costs 78.98 ms and 4.63 ms to train and test a Chinese sentence of 17.9 words. The method is a new way to parse the phrase structure grammar for Chinese, and has good generalization ability and fast speed.

Original languageEnglish
Pages (from-to)519-525
Number of pages7
JournalJournal of Beijing Institute of Technology (English Edition)
Volume24
Issue number4
DOIs
Publication statusPublished - 1 Dec 2015

Keywords

  • Conditional random field
  • Phrase structure grammar
  • Syntactic parsing
  • Syntactic tree

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