@inproceedings{constant-tellier-2012-evaluating,
title = "Evaluating the Impact of External Lexical Resources into a {CRF}-based Multiword Segmenter and Part-of-Speech Tagger",
author = "Constant, Matthieu and
Tellier, Isabelle",
editor = "Calzolari, Nicoletta and
Choukri, Khalid and
Declerck, Thierry and
Do{\u{g}}an, Mehmet U{\u{g}}ur and
Maegaard, Bente and
Mariani, Joseph and
Moreno, Asuncion and
Odijk, Jan and
Piperidis, Stelios",
booktitle = "Proceedings of the Eighth International Conference on Language Resources and Evaluation ({LREC}'12)",
month = may,
year = "2012",
address = "Istanbul, Turkey",
publisher = "European Language Resources Association (ELRA)",
url = "http://www.lrec-conf.org/proceedings/lrec2012/pdf/610_Paper.pdf",
pages = "646--650",
abstract = "This paper evaluates the impact of external lexical resources into a CRF-based joint Multiword Segmenter and Part-of-Speech Tagger. We especially show different ways of integrating lexicon-based features in the tagging model. We display an absolute gain of 0.5{\%} in terms of f-measure. Moreover, we show that the integration of lexicon-based features significantly compensates the use of a small training corpus.",
}
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%0 Conference Proceedings
%T Evaluating the Impact of External Lexical Resources into a CRF-based Multiword Segmenter and Part-of-Speech Tagger
%A Constant, Matthieu
%A Tellier, Isabelle
%Y Calzolari, Nicoletta
%Y Choukri, Khalid
%Y Declerck, Thierry
%Y Doğan, Mehmet Uğur
%Y Maegaard, Bente
%Y Mariani, Joseph
%Y Moreno, Asuncion
%Y Odijk, Jan
%Y Piperidis, Stelios
%S Proceedings of the Eighth International Conference on Language Resources and Evaluation (LREC’12)
%D 2012
%8 May
%I European Language Resources Association (ELRA)
%C Istanbul, Turkey
%F constant-tellier-2012-evaluating
%X This paper evaluates the impact of external lexical resources into a CRF-based joint Multiword Segmenter and Part-of-Speech Tagger. We especially show different ways of integrating lexicon-based features in the tagging model. We display an absolute gain of 0.5% in terms of f-measure. Moreover, we show that the integration of lexicon-based features significantly compensates the use of a small training corpus.
%U http://www.lrec-conf.org/proceedings/lrec2012/pdf/610_Paper.pdf
%P 646-650
Markdown (Informal)
[Evaluating the Impact of External Lexical Resources into a CRF-based Multiword Segmenter and Part-of-Speech Tagger](http://www.lrec-conf.org/proceedings/lrec2012/pdf/610_Paper.pdf) (Constant & Tellier, LREC 2012)
ACL