Exact Inference for Generative Probabilistic Non-Projective Dependency Parsing

Shay B. Cohen, Carlos Gómez-Rodríguez, Giorgio Satta

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

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.
Original languageEnglish
Title of host publicationProceedings of the 2011 Conference on Empirical Methods in Natural Language Processing
Place of PublicationEdinburgh, Scotland, UK.
PublisherAssociation for Computational Linguistics
Number of pages12
ISBN (Print)978-1-937284-11-4
Publication statusPublished - 1 Jul 2011


Dive into the research topics of 'Exact Inference for Generative Probabilistic Non-Projective Dependency Parsing'. Together they form a unique fingerprint.

Cite this