Learning efficient parsing

Authors:
Gertjan van Noord
Affiliations:
University of Groningen
Venue:
EACL '09 Proceedings of the 12th Conference of the European Chapter of the Association for Computational Linguistics
Year:
2009

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Abstract

A corpus-based technique is described to improve the efficiency of wide-coverage high-accuracy parsers. By keeping track of the derivation steps which lead to the best parse for a very large collection of sentences, the parser learns which parse steps can be filtered without significant loss in parsing accuracy, but with an important increase in parsing efficiency. An interesting characteristic of our approach is that it is self-learning, in the sense that it uses unannotated corpora.