@inproceedings{pradet-etal-2014-adapting,
title = "Adapting {V}erb{N}et to {F}rench using existing resources",
author = {Pradet, Quentin and
Danlos, Laurence and
de Chalendar, Ga{\"e}l},
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Declerck, Thierry and
Loftsson, Hrafn and
Maegaard, Bente and
Mariani, Joseph and
Moreno, Asuncion and
Odijk, Jan and
Piperidis, Stelios",
booktitle = "Proceedings of the Ninth International Conference on Language Resources and Evaluation ({LREC}'14)",
month = may,
year = "2014",
address = "Reykjavik, Iceland",
publisher = "European Language Resources Association (ELRA)",
url = "http://www.lrec-conf.org/proceedings/lrec2014/pdf/203_Paper.pdf",
pages = "1122--1126",
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 doesnt exist for other languages, despite some (mostly automatic and unsupervised) attempts. We show how to semi-automatically adapt VerbNet using existing resources designed for di{\"\i}{\neg}erent purposes. This study focuses on French and uses two French resources: a semantic lexicon (Les Verbes Fran{\c{c}}ais) and a syntactic lexicon (Lexique-Grammaire).},
}
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<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 doesnt exist for other languages, despite some (mostly automatic and unsupervised) attempts. We show how to semi-automatically adapt VerbNet using existing resources designed for diïʼnegerent purposes. This study focuses on French and uses two French resources: a semantic lexicon (Les Verbes Français) and a syntactic lexicon (Lexique-Grammaire).</abstract>
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%0 Conference Proceedings
%T Adapting VerbNet to French using existing resources
%A Pradet, Quentin
%A Danlos, Laurence
%A de Chalendar, Gaël
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Declerck, Thierry
%Y Loftsson, Hrafn
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Moreno, Asuncion
%Y Odijk, Jan
%Y Piperidis, Stelios
%S Proceedings of the Ninth International Conference on Language Resources and Evaluation (LREC’14)
%D 2014
%8 May
%I European Language Resources Association (ELRA)
%C Reykjavik, Iceland
%F pradet-etal-2014-adapting
%X 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 doesnt exist for other languages, despite some (mostly automatic and unsupervised) attempts. We show how to semi-automatically adapt VerbNet using existing resources designed for diïʼnegerent purposes. This study focuses on French and uses two French resources: a semantic lexicon (Les Verbes Français) and a syntactic lexicon (Lexique-Grammaire).
%U http://www.lrec-conf.org/proceedings/lrec2014/pdf/203_Paper.pdf
%P 1122-1126
Markdown (Informal)
[Adapting VerbNet to French using existing resources](http://www.lrec-conf.org/proceedings/lrec2014/pdf/203_Paper.pdf) (Pradet et al., LREC 2014)
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).