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Author
F. Sangati
W. Zuidema
R. Bod
Year
2009
Title
A generative re-ranking model for dependency parsing
Event
11th International Conference on Parsing Technologies (IWPT-09), Paris, France
Book/source title
Proceedings of the 11th International Conference on Parsing Technologies, IWPT-09: 7-9 October 2009, Paris, France
Pages (from-to)
238-241
Publisher
Morristown, NJ: Association for Computational Linguistics (ACL)
Document type
Conference contribution
Faculty
Interfacultary Research Institutes
Institute
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.
Link
Link
Language
Undefined/Unknown
Permalink
http://hdl.handle.net/11245/1.315525
Downloads
  • 315525.pdf

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