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Constructing a lexicon of Arabic-English named entity using SMT and semantic linked data
Joint Authors
Hkiri, Emna
Mallat, Suhayl
Zrigui, Munir
Source
The International Arab Journal of Information Technology
Issue
Vol. 14, Issue 6 (30 Nov. 2017)6 p.
Publisher
Publication Date
2017-11-30
Country of Publication
Jordan
No. of Pages
6
Main Subjects
Information Technology and Computer Science
Abstract EN
Named entity recognition is the problem of locating and categorizing atomic entities in a given text.
In this work, we used DBpedia Linked datasets and combined existing open source tools to generate from a parallel corpus a bilingual lexicon of Named Entities (NE).
To annotate NE in the monolingual English corpus, we used linked data entities by mapping them to Gate Gazetteers.
In order to translate entities identified by the gate tool from the English corpus, we used moses, a statistical machine translation system.
The construction of the Arabic-English named entities lexicon is based on the results of moses translation.
Our method is fully automatic and aims to help Natural Language Processing (NLP) tasks such as, machine translation information retrieval, text mining and question answering.
Our lexicon contains 48753 pairs of Arabic-English NE, it is freely available for use by other researchers
American Psychological Association (APA)
Hkiri, Emna& Mallat, Suhayl& Zrigui, Munir. 2017. Constructing a lexicon of Arabic-English named entity using SMT and semantic linked data. The International Arab Journal of Information Technology،Vol. 14, no. 6.
https://search.emarefa.net/detail/BIM-853091
Modern Language Association (MLA)
Hkiri, Emna…[et al.]. Constructing a lexicon of Arabic-English named entity using SMT and semantic linked data. The International Arab Journal of Information Technology Vol. 14, no. 6 (Nov. 2017).
https://search.emarefa.net/detail/BIM-853091
American Medical Association (AMA)
Hkiri, Emna& Mallat, Suhayl& Zrigui, Munir. Constructing a lexicon of Arabic-English named entity using SMT and semantic linked data. The International Arab Journal of Information Technology. 2017. Vol. 14, no. 6.
https://search.emarefa.net/detail/BIM-853091
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-853091