@inproceedings{couto-etal-2010-oal,
title = "{OAL}: A {NLP} Architecture to Improve the Development of Linguistic Resources for {NLP}",
author = "Couto, Javier and
Blancafort, Helena and
Seng, Somara and
Kuchmann-Beauger, Nicolas and
Talby, Anass and
de Loupy, Claude",
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Maegaard, Bente and
Mariani, Joseph and
Odijk, Jan and
Piperidis, Stelios and
Rosner, Mike and
Tapias, Daniel",
booktitle = "Proceedings of the Seventh International Conference on Language Resources and Evaluation ({LREC}'10)",
month = may,
year = "2010",
address = "Valletta, Malta",
publisher = "European Language Resources Association (ELRA)",
url = "http://www.lrec-conf.org/proceedings/lrec2010/pdf/882_Paper.pdf",
abstract = "The performance of most NLP applications relies upon the quality of linguistic resources. The creation, maintenance and enrichment of those resources are a labour-intensive task, especially when no tools are available. In this paper we present the NLP architecture OAL, designed to assist computational linguists in the whole process of the development of resources in an industrial context: from corpora compilation to quality assurance. To add new words more easily to the morphosyntactic lexica, a guesser that lemmatizes and assigns morphosyntactic tags as well as inflection paradigms to a new word has been developed. Moreover, different control mechanisms are set up to check the coherence and consistency of the resources. Today OAL manages resources in five European languages: French, English, Spanish, Italian and Polish. Chinese and Portuguese are in process. The development of OAL has followed an incremental strategy. At present, semantic lexica, a named entities guesser and a named entities phonetizer are being developed.",
}
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<abstract>The performance of most NLP applications relies upon the quality of linguistic resources. The creation, maintenance and enrichment of those resources are a labour-intensive task, especially when no tools are available. In this paper we present the NLP architecture OAL, designed to assist computational linguists in the whole process of the development of resources in an industrial context: from corpora compilation to quality assurance. To add new words more easily to the morphosyntactic lexica, a guesser that lemmatizes and assigns morphosyntactic tags as well as inflection paradigms to a new word has been developed. Moreover, different control mechanisms are set up to check the coherence and consistency of the resources. Today OAL manages resources in five European languages: French, English, Spanish, Italian and Polish. Chinese and Portuguese are in process. The development of OAL has followed an incremental strategy. At present, semantic lexica, a named entities guesser and a named entities phonetizer are being developed.</abstract>
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%0 Conference Proceedings
%T OAL: A NLP Architecture to Improve the Development of Linguistic Resources for NLP
%A Couto, Javier
%A Blancafort, Helena
%A Seng, Somara
%A Kuchmann-Beauger, Nicolas
%A Talby, Anass
%A de Loupy, Claude
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Odijk, Jan
%Y Piperidis, Stelios
%Y Rosner, Mike
%Y Tapias, Daniel
%S Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC’10)
%D 2010
%8 May
%I European Language Resources Association (ELRA)
%C Valletta, Malta
%F couto-etal-2010-oal
%X The performance of most NLP applications relies upon the quality of linguistic resources. The creation, maintenance and enrichment of those resources are a labour-intensive task, especially when no tools are available. In this paper we present the NLP architecture OAL, designed to assist computational linguists in the whole process of the development of resources in an industrial context: from corpora compilation to quality assurance. To add new words more easily to the morphosyntactic lexica, a guesser that lemmatizes and assigns morphosyntactic tags as well as inflection paradigms to a new word has been developed. Moreover, different control mechanisms are set up to check the coherence and consistency of the resources. Today OAL manages resources in five European languages: French, English, Spanish, Italian and Polish. Chinese and Portuguese are in process. The development of OAL has followed an incremental strategy. At present, semantic lexica, a named entities guesser and a named entities phonetizer are being developed.
%U http://www.lrec-conf.org/proceedings/lrec2010/pdf/882_Paper.pdf
Markdown (Informal)
[OAL: A NLP Architecture to Improve the Development of Linguistic Resources for NLP](http://www.lrec-conf.org/proceedings/lrec2010/pdf/882_Paper.pdf) (Couto et al., LREC 2010)
ACL