DarNERcorp: An annotated named entity recognition dataset in the Moroccan dialect

Hanane Nour Moussa; Asmaa Mourhir

doi:10.1016/j.dib.2023.109234

DarNERcorp: An annotated named entity recognition dataset in the Moroccan dialect

Data Brief. 2023 May 12:48:109234. doi: 10.1016/j.dib.2023.109234. eCollection 2023 Jun.

Authors

Hanane Nour Moussa¹, Asmaa Mourhir¹

Affiliation

¹ School of Science and Engineering, Al Akhawayn University in Ifrane, P.O. Box 104, Hassan II Avenue, Ifrane 53000, Morocco.

Abstract

DarNERcorp is a manually annotated named entity recognition (NER) dataset in the Moroccan dialect, also called Darija. The dataset consists of 65,905 tokens and their corresponding tags according to BIO scheme. 13.8% of the tokens are named entities spanning four categories: person, location, organization, and miscellaneous. The data were scraped from the Moroccan Dialect section of Wikipedia and processed and annotated using open-source libraries and tools. The data are useful for the Arabic natural language processing (NLP) community as they address the lack in dialectal Arabic annotated corpora. This dataset can be used to train and evaluate named entity recognition systems in dialectal and mixed Arabic.

Keywords: BIO; Corpus; Dialectal Arabic; Named entity recognition; Natural language processing; Text mining.