We describe a generative model for non- projective dependency parsing based on a simplified version of a transition system that has recently appeared in the literature. We then develop a dynamic programming parsing algorithm for our model, and derive an inside-outside algorithm that can be used for unsupervised learning of non-projective dependency trees.

Exact Inference for Generative Probabilistic Non-Projective Dependency Parsing

SATTA, GIORGIO
2011

Abstract

We describe a generative model for non- projective dependency parsing based on a simplified version of a transition system that has recently appeared in the literature. We then develop a dynamic programming parsing algorithm for our model, and derive an inside-outside algorithm that can be used for unsupervised learning of non-projective dependency trees.
2011
Proceedings of the Conference on Empirical Methods in Natural Language Processing
9781937284114
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11577/175473
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