Treebank-Based Acquisition of LFG Parsing Resources for French

Natalie Schluter, Josef van Genabith

Abstract
Motivated by the expense in time and other resources to produce hand-crafted grammars, there has been increased interest in automatically obtained wide-coverage grammars from treebanks for natural language processing. In particular, recent years have seen the growth in interest in automatically obtained deep resources that can represent information absent from simple CFG-type structured treebanks and which are considered to produce more language-neutral linguistic representations, such as dependency syntactic trees. As is often the case in early pioneering work on natural language processing, English has provided the focus of first efforts towards acquiring deep-grammar resources, followed by successful treatments of, for example, German, Japanese, Chinese and Spanish. However, no comparable large-scale automatically acquired deep-grammar resources have been obtained for French to date. The goal of this paper is to present the application of treebank-based language acquisition to the case of French. We show that with modest changes to the established parsing architectures, encouraging results can be obtained for French, with an overall best dependency structure f-score of 86.73%.
Anthology ID:
L08-1246
Volume:
Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)
Month:
May
Year:
2008
Address:
Marrakech, Morocco
Venue:
LREC
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Publisher:
European Language Resources Association (ELRA)
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URL:
http://www.lrec-conf.org/proceedings/lrec2008/pdf/739_paper.pdf
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Cite (ACL):
Natalie Schluter and Josef van Genabith. 2008. Treebank-Based Acquisition of LFG Parsing Resources for French. In Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08), Marrakech, Morocco. European Language Resources Association (ELRA).
Cite (Informal):
Treebank-Based Acquisition of LFG Parsing Resources for French (Schluter & van Genabith, LREC 2008)
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http://www.lrec-conf.org/proceedings/lrec2008/pdf/739_paper.pdf
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