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        <title>Adapting a resource-light highly multilingual Named Entity Recognition system to Arabic</title>
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            <title>Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC’10)</title>
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    <abstract>We present a fully functional Arabic information extraction (IE) system that is used to analyze large volumes of news texts every day to extract the named entity (NE) types person, organization, location, date and number, as well as quotations (direct reported speech) by and about people. The Named Entity Recognition (NER) system was not developed for Arabic, but - instead - a highly multilingual, almost language-independent NER system was adapted to also cover Arabic. The Semitic language Arabic substantially differs from the Indo-European and Finno-Ugric languages currently covered. This paper thus describes what Arabic language-specific resources had to be developed and what changes needed to be made to the otherwise language-independent rule set in order to be applicable to the Arabic language. The achieved evaluation results are generally satisfactory, but could be improved for certain entity types. The results of the IE tools can be seen on the Arabic pages of the freely accessible Europe Media Monitor (EMM) application NewsExplorer, which can be found at http://press.jrc.it/overview.html.</abstract>
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%0 Conference Proceedings
%T Adapting a resource-light highly multilingual Named Entity Recognition system to Arabic
%A Zaghouani, Wajdi
%A Pouliquen, Bruno
%A Ebrahim, Mohamed
%A Steinberger, Ralf
%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 zaghouani-etal-2010-adapting
%X We present a fully functional Arabic information extraction (IE) system that is used to analyze large volumes of news texts every day to extract the named entity (NE) types person, organization, location, date and number, as well as quotations (direct reported speech) by and about people. The Named Entity Recognition (NER) system was not developed for Arabic, but - instead - a highly multilingual, almost language-independent NER system was adapted to also cover Arabic. The Semitic language Arabic substantially differs from the Indo-European and Finno-Ugric languages currently covered. This paper thus describes what Arabic language-specific resources had to be developed and what changes needed to be made to the otherwise language-independent rule set in order to be applicable to the Arabic language. The achieved evaluation results are generally satisfactory, but could be improved for certain entity types. The results of the IE tools can be seen on the Arabic pages of the freely accessible Europe Media Monitor (EMM) application NewsExplorer, which can be found at http://press.jrc.it/overview.html.
%U http://www.lrec-conf.org/proceedings/lrec2010/pdf/669_Paper.pdf

Markdown (Informal)

[Adapting a resource-light highly multilingual Named Entity Recognition system to Arabic](http://www.lrec-conf.org/proceedings/lrec2010/pdf/669_Paper.pdf) (Zaghouani et al., LREC 2010)

• Adapting a resource-light highly multilingual Named Entity Recognition system to Arabic (Zaghouani et al., LREC 2010)

ACL

• Wajdi Zaghouani, Bruno Pouliquen, Mohamed Ebrahim, and Ralf Steinberger. 2010. Adapting a resource-light highly multilingual Named Entity Recognition system to Arabic. In Proceedings of the Seventh International Conference on Language Resources and Evaluation (LREC'10), Valletta, Malta. European Language Resources Association (ELRA).