A Learning Approach to Shallow Parsing

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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 better learned using open/close predictors than using inside/outside predictors.
LaTex 2e, 11 pages, 2 eps figures, 1 bbl file, uses colacl.sty

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Machine Learning, Computation and Language, I.2.6; I.2.7

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http://salesiana.dossiersoluciones.com/handle/123456789/30370

Consulte el texto completo en el siguiente enlace:

https://arxiv.org/abs/cs/0008022
 http://arxiv.org/abs/cs/0008022
 Proceedings of EMNLP-VLC'99, pages 168-178

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arXiv