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Integrating Graph-Based and Transition-Based Dependency Parsers
Uppsala University, Disciplinary Domain of Humanities and Social Sciences, Faculty of Languages, Department of Linguistics and Philology. (Computational linguistics)
Google Research.
2008 (English)In: Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies (ACL-08: HLT), Stroudsburg, PA: Association for Computational Linguistics (ACL) , 2008, 950-958 p.Conference paper, Published paper (Refereed)
Abstract [en]

Previous studies of data-driven dependency parsing have shown that the distribution of parsing errors are correlated with theoretical properties of the models used for learning and inference. In this paper, we show how these results can be exploited to improve parsing accuracy by integrating a graph-based and a transition-based model. By letting one model generate features for the other, we consistently improve accuracy for both models, resulting in a significant improvement of the state of the art when evaluated on data sets from the CoNLL-X shared task.

Place, publisher, year, edition, pages
Stroudsburg, PA: Association for Computational Linguistics (ACL) , 2008. 950-958 p.
Series
Proceedings of the Association for Computational Linguistics, ISSN 0736-587X
National Category
Language Technology (Computational Linguistics) Language Technology (Computational Linguistics)
Research subject
Computational Linguistics
Identifiers
URN: urn:nbn:se:uu:diva-87660ISBN: 978-1-932432-04-6 (print)OAI: oai:DiVA.org:uu-87660DiVA: diva2:132991
Conference
46th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies (ACL-08: HLT), 15-20 June, Columbus, OH
Available from: 2009-01-07 Created: 2009-01-07 Last updated: 2011-06-07Bibliographically approved

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Nivre, Joakim

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  • apa
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Language
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  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
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Output format
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