Bagging and Boosting a Treebank Parser
<|reference_start|>Bagging and Boosting a Treebank Parser: 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.<|reference_end|>
@article{henderson2000bagging,
    title={Bagging and Boosting a Treebank Parser},
    author={John C. Henderson and Eric Brill},
    journal={Proceedings of the 1st Meeting of the North American Chapter of
  the Association for Computational Linguistics (NAACL-2000), pages 34-41},
    year={2000},
    archivePrefix={arXiv},
    eprint={cs/0006011},
    primaryClass={cs.CL}
}