Title: Adapting a resource-light highly multilingual Named Entity Recognition system to Arabic
Authors: ZAGHOUANI WajdiPOULIQUEN BrunoEBRAHIM MOHAMEDSTEINBERGER Ralf
Citation: Proceedings of The seventh international conference on Language Resources and Evaluation (LREC) - ISBN 2-9517408-6-7 p. 563-567
Publisher: European Language Resources Agency (ELRA)
Publication Year: 2010
JRC N°: JRC57133
URI: http://www.lrec-conf.org/proceedings/lrec2010/index.html
http://publications.jrc.ec.europa.eu/repository/handle/JRC57133
Type: Contributions to Conferences
Abstract: We present a working Arabic information extraction (IE) system that is used to analyze large volumes of news texts every day to extract the named entity types person, organization, location, date and number, as well as quotations (reported speech) by and about people. The NER system was not developed for Arabic, but - instead - a highly multilingual, almost language-independent NER system was adapted to also cover Arabic. 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.
JRC Institute:Institute for the Protection and Security of the Citizen

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