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EDRAK: Entity-Centric Data Resource for Arabic Knowledge
2015
Proceedings of the Second Workshop on Arabic Natural Language Processing
Online Arabic content is growing very rapidly, with unmatched growth in Arabic structured resources. Systems that perform standard Natural Language Processing (NLP) tasks such as Named Entity Disambiguation (NED) struggle to deliver decent quality due to the lack of rich Arabic entity repositories. In this paper, we introduce EDRAK, an automatically generated comprehensive Arabic entity-centric resource. EDRAK contains more than two million entities together with their Arabic names and
doi:10.18653/v1/w15-3224
dblp:conf/wanlp/Gad-ElrabYW15
fatcat:ot4im7rl2rg4lf4j6hglmdpswq