Year: 2015
Type: conference-paper
Abstract: 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 contextual keyphrases.Manual evaluation confirmed the quality of the generated data.We are making EDRAK publicly available as a valuable resource to help advance research in Arabic NLP and IR tasks such as dictionary-based Named-Entity Recognition, entity classification, and entity summarization.
DOI: 10.18653/v1/w15-3224
Institution: Max Planck Institute for Informatics
Language: English
Topic: Topic Modeling
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W2250865411