Text Chunking Using Transformation-Based Learning

by: Lance Ramshaw, Mitch Marcus

edited by: David Yarovsky, Kenneth Church

(1995), pp. 82-94.

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Abstract

Eric Brill introduced transformation-based learning and showed that it can do part-ofspeech tagging with fairly high accuracy. The same method can be applied at a higher level of textual interpretation for locating chunks in the tagged text, including non-recursive "baseNP" chunks. For this purpose, it is convenient to view chunking as a tagging problem by encoding the chunk structure in new tags attached to each word. In automatic tests using Treebank-derived data, this technique achieved ...

@inproceedings{citeulike:176907, abstract = {Eric Brill introduced transformation-based learning and showed that it can do part-ofspeech tagging with fairly high accuracy. The same method can be applied at a higher level of textual interpretation for locating chunks in the tagged text, including non-recursive \"baseNP\" chunks. For this purpose, it is convenient to view chunking as a tagging problem by encoding the chunk structure in new tags attached to each word. In automatic tests using Treebank-derived data, this technique achieved ...}, address = {Somerset, New Jersey}, author = {Ramshaw, Lance and Marcus, Mitch }, booktitle = {Proceedings of the Third Workshop on Very Large Corpora}, citeulike-article-id = {176907}, editor = {Yarovsky, David and Church, Kenneth }, keywords = {chunk, ml, nlp, parsing, tbl}, pages = {82--94}, posted-at = {2007-04-24 14:28:37}, priority = {2}, publisher = {Association for Computational Linguistics}, title = {Text Chunking Using Transformation-Based Learning}, url = {http://citeseer.ist.psu.edu/ramshaw95text.html}, year = {1995} }

RIS record

TY - CONF ID - citeulike:176907 L3 - citeulike-article-id:176907 TI - Text Chunking Using Transformation-Based Learning T2 - Proceedings of the Third Workshop on Very Large Corpora SP - 82 EP - 94 AD - Somerset, New Jersey PB - Association for Computational Linguistics N2 - Eric Brill introduced transformation-based learning and showed that it can do part-ofspeech tagging with fairly high accuracy. The same method can be applied at a higher level of textual interpretation for locating chunks in the tagged text, including non-recursive "baseNP" chunks. For this purpose, it is convenient to view chunking as a tagging problem by encoding the chunk structure in new tags attached to each word. In automatic tests using Treebank-derived data, this technique achieved ... KW - chunk KW - ml KW - nlp KW - parsing KW - tbl AU - Ramshaw, Lance AU - Marcus, Mitch A2 - Yarovsky, David A2 - Church, Kenneth PY - 1995/// UR - http://citeseer.ist.psu.edu/ramshaw95text.html ER -

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