A generative re-ranking model for dependency parsing

Open Access
Authors
Publication date 2009
Book title Proceedings of the 11th International Conference on Parsing Technologies, IWPT-09: 7-9 October 2009, Paris, France
Event 11th International Conference on Parsing Technologies (IWPT-09), Paris, France
Pages (from-to) 238-241
Publisher Morristown, NJ: Association for Computational Linguistics (ACL)
Organisations
  • Interfacultary Research - Institute for Logic, Language and Computation (ILLC)
Abstract We propose a framework for dependency parsing based on a combination of discriminative and generative models. We use a discriminative model to obtain a k-best list of candidate parses, and subsequently rerank those candidates using a generative model. We show how this approach allows us to evaluate a variety of generative models, without needing different parser implementations. Moreover, we present empirical results that show a small improvement over state-of-the-art dependency parsing of English sentences.
Document type Conference contribution
Published at http://portal.acm.org/citation.cfm?id=1697285
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315525.pdf (Final published version)
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