Abstract
This paper introduces a first step towards creating the NERDz dataset. A manually annotated dataset of named entities for the Algerian vernacular dialect. The annotations are built on top of a recent extension to the Algerian NArabizi Treebank, comprizing NArabizi sentences with manual transliterations into Arabic and code-switched scripts. NERDz is therefore not only the first dataset of named entities for Algerian, but it also comprises parallel entities written in Latin, Arabic, and code-switched scripts. We present a detailed overview of our annotations, inter-annotator agreement measures, and define two preliminary baselines using a neural sequence labeling approach and an Algerian BERT model. We also make the annotation guidelines and the annotations available for future work.
Cite
CITATION STYLE
Touileb, S. (2022). NERDz: A Preliminary Dataset of Named Entities for Algerian. In Proceedings of the 2nd Conference of the Asia-Pacific Chapter of the Association for Computational Linguistics and the 12th International Joint Conference on Natural Language Processing: Long Paper, AACL-IJCNLP 2022 (Vol. 3, pp. 95–101). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2022.aacl-short.13
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