Bagging and Boosting a Treebank Parser

Details Bagging and Boosting a Treebank Parser Bagging and Boosting a Treebank Parser

2000-06-05

arxiv.org/abs/cs/0006011v1

Proceedings of the 1st Meeting of the North American Chapter of the Association for Computational Linguistics (NAACL-2000), pa

Computer Science

Computation and Language

8 pages

Scientific paper

Bagging and boosting, two effective machine learning techniques, are applied to natural language parsing. Experiments using these techniques with a trainable statistical parser are described. The best resulting system provides roughly as large of a gain in F-measure as doubling the corpus size. Error analysis of the result of the boosting technique reveals some inconsistent annotations in the Penn Treebank, suggesting a semi-automatic method for finding inconsistent treebank annotations.

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