Name: WDC
Description: contains around
  6 million tokens representing different genres, as
  Wikipedia is considered an open domain
Provider: University of Essex
Paper Title: Automatic Creation of Arabic Named Entity Annotated Corpus Using
  Wikipedia
Tasks: named entity recognition
Venue Name: European Chapter of the Association for Computational Linguistics
Authors: M. Althobaiti,Udo Kruschwitz,Massimo Poesio
Abstract: In this paper we propose a new methodology to exploit Wikipedia features and structure to automatically develop an Arabic NE annotated corpus. Each Wikipedia link is transformed into an NE type of the target article in order to produce the NE annotation. Other Wikipedia features - namely redirects, anchor texts, and inter-language links - are used to tag additional NEs, which appear without links in Wikipedia texts. Furthermore, we have developed a filtering algorithm to eliminate ambiguity when tagging candidate NEs. Herein we also introduce a mechanism based on the high coverage of Wikipedia in order to address two challenges particular to tagging NEs in Arabic text: rich morphology and the absence of capitalisation. The corpus created with our new method (WDC) has been used to train an NE tagger which has been tested on different domains. Judging by the results, an NE tagger trained on WDC can compete with those trained on manually annotated corpora.