Dependency parsing and projection based on word-pair classification

  • Authors:
  • Wenbin Jiang;Qun Liu

  • Affiliations:
  • Chinese Academy of Sciences, Beijing, China;Chinese Academy of Sciences, Beijing, China

  • Venue:
  • ACL '10 Proceedings of the 48th Annual Meeting of the Association for Computational Linguistics
  • Year:
  • 2010

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Abstract

In this paper we describe an intuitionistic method for dependency parsing, where a classifier is used to determine whether a pair of words forms a dependency edge. And we also propose an effective strategy for dependency projection, where the dependency relationships of the word pairs in the source language are projected to the word pairs of the target language, leading to a set of classification instances rather than a complete tree. Experiments show that, the classifier trained on the projected classification instances significantly outperforms previous projected dependency parsers. More importantly, when this classifier is integrated into a maximum spanning tree (MST) dependency parser, obvious improvement is obtained over the MST baseline.