Definition Extraction Using a Sequential Combination of Baseline Grammars and Machine Learning Classifiers

Łukasz Degórski, Michał Marcińczuk, Adam Przepiórkowski


Abstract
The paper deals with the task of definition extraction from a small and noisy corpus of instructive texts. Three approaches are presented: Partial Parsing, Machine Learning and a sequential combination of both. We show that applying ML methods with the support of a trivial grammar gives results better than a relatively complicated partial grammar, and much better than pure ML approach.
Anthology ID:
L08-1294
Volume:
Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)
Month:
May
Year:
2008
Address:
Marrakech, Morocco
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
Language:
URL:
http://www.lrec-conf.org/proceedings/lrec2008/pdf/213_paper.pdf
DOI:
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PDF:
http://www.lrec-conf.org/proceedings/lrec2008/pdf/213_paper.pdf