Dependency Parsing with Short Dependency Relations in Unlabeled Data

Wenliang Chen, Daisuke Kawahara, Kiyotaka Uchimoto, Yujie Zhang, Hitoshi Isahara

Research output: Chapter in Book/Report/Conference proceedingConference contribution

16 Citations (Scopus)

Abstract

This paper presents an effective dependency parsing approach of incorporating short dependency information from unlabeled data. The unlabeled data is automatically parsed by a deterministic dependency parser, which can provide relatively high performance for short dependencies between words. We then train another parser which uses the information on short dependency relations extracted from the output of the first parser. Our proposed approach achieves an unlabeled attachment score of 86.52, an absolute 1.24% improvement over the baseline system on the data set of Chinese Treebank.

Original languageEnglish
Title of host publicationIJCNLP 2008 - 3rd International Joint Conference on Natural Language Processing, Proceedings of the Conference
PublisherAssociation for Computational Linguistics (ACL)
Pages88-94
Number of pages7
ISBN (Electronic)9780000000002
Publication statusPublished - 2008
Event3rd International Joint Conference on Natural Language Processing, IJCNLP 2008 - Hyderabad, India
Duration: 2008 Jan 72008 Jan 12

Publication series

NameIJCNLP 2008 - 3rd International Joint Conference on Natural Language Processing, Proceedings of the Conference
Volume1

Conference

Conference3rd International Joint Conference on Natural Language Processing, IJCNLP 2008
Country/TerritoryIndia
CityHyderabad
Period08/1/708/1/12

ASJC Scopus subject areas

  • Language and Linguistics
  • Linguistics and Language

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