A Learning Approach to Shallow Parsing (1999)
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| Venue: | IN PROCEEDINGS OF EMNLP-WVLC'99. ASSOCIATION FOR COMPUTATIONAL LINGUISTICS |
| Citations: | 57 - 23 self |
BibTeX
@INPROCEEDINGS{Muñoz99alearning,
author = {Marcia Muñoz and Vasin Punyakanok and Dan Roth and Day Zimak},
title = {A Learning Approach to Shallow Parsing},
booktitle = {IN PROCEEDINGS OF EMNLP-WVLC'99. ASSOCIATION FOR COMPUTATIONAL LINGUISTICS},
year = {1999},
publisher = {}
}
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Abstract
A SNoW based learning approach to shallow parsing tasks is presented and studied experimentally. The approach learns to identify syntactic patterns by combining simple predictors to produce a coherent inference. Two instantiations of this approach are studied and experimental results for Noun-Phrases (NP) and Subject-Verb (SV) phrases that compare favorably with the best published results are presented. In doing that, we compare two ways of modeling the problem of learning to recognize patterns and suggest that shallow parsing patterns are bet- ter learned using open/close predictors than using inside/outside predictors.
