Adapting VerbNet to French using existing resources

Quentin Pradet, Laurence Danlos, Gaël de Chalendar


Abstract
VerbNet is an English lexical resource for verbs that has proven useful for English NLP due to its high coverage and coherent classification. Such a resource doesn’t exist for other languages, despite some (mostly automatic and unsupervised) attempts. We show how to semi-automatically adapt VerbNet using existing resources designed for different purposes. This study focuses on French and uses two French resources: a semantic lexicon (Les Verbes Français) and a syntactic lexicon (Lexique-Grammaire).
Anthology ID:
L14-1204
Volume:
Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14)
Month:
May
Year:
2014
Address:
Reykjavik, Iceland
Editors:
Nicoletta Calzolari, Khalid Choukri, Thierry Declerck, Hrafn Loftsson, Bente Maegaard, Joseph Mariani, Asuncion Moreno, Jan Odijk, Stelios Piperidis
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
1122–1126
Language:
URL:
http://www.lrec-conf.org/proceedings/lrec2014/pdf/203_Paper.pdf
DOI:
Bibkey:
Cite (ACL):
Quentin Pradet, Laurence Danlos, and Gaël de Chalendar. 2014. Adapting VerbNet to French using existing resources. In Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC'14), pages 1122–1126, Reykjavik, Iceland. European Language Resources Association (ELRA).
Cite (Informal):
Adapting VerbNet to French using existing resources (Pradet et al., LREC 2014)
Copy Citation:
PDF:
http://www.lrec-conf.org/proceedings/lrec2014/pdf/203_Paper.pdf