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Improving Chinese POS Tagging with Dependency Parsing

  • School of Computer Science and Technology, Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Recent research usually models POS tagging as a sequential labeling problem, in which only local context features can be used. Due to the lack of morphological inflections, many tagging ambiguities in Chinese are difficult to handle unless consulting larger contexts. In this paper, we try to improve Chinese POS tagging by using long-distance dependencies produced by a statistical dependency parser. Experimental results show that, despite error propagation, the syntactic features can significantly improve the tagging accuracy from 93.88% to 94.41% (p < 10-5). Detailed analysis shows that these features are helpful for ambiguous pairs like {NN,VV} and {DEC,DEG}.

Original languageEnglish
Title of host publicationIJCNLP 2011 - Proceedings of the 5th International Joint Conference on Natural Language Processing
EditorsHaifeng Wang, David Yarowsky
PublisherAssociation for Computational Linguistics (ACL)
Pages1447-1451
Number of pages5
ISBN (Electronic)9789744665645
StatePublished - 2011
Externally publishedYes
Event5th International Joint Conference on Natural Language Processing, IJCNLP 2011 - Chiang Mai, Thailand
Duration: 8 Nov 201113 Nov 2011

Publication series

NameIJCNLP 2011 - Proceedings of the 5th International Joint Conference on Natural Language Processing

Conference

Conference5th International Joint Conference on Natural Language Processing, IJCNLP 2011
Country/TerritoryThailand
CityChiang Mai
Period8/11/1113/11/11

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