May 13, 2022, 1:11 a.m. | Abdullah Aldumaykhi, Saad Otai, Abdulkareem Alsudais

cs.CL updates on arXiv.org arxiv.org

The main objective of this paper is to compare and evaluate the performances
of three open Arabic NER tools: CAMeL, Hatmi, and Stanza. We collected a corpus
consisting of 30 articles written in MSA and manually annotated all the
entities of the person, organization, and location types at the article
(document) level. Our results suggest a similarity between Stanza and Hatmi
with the latter receiving the highest F1 score for the three entity types.
However, CAMeL achieved the highest precision …

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