Arabic Named Entity Recognition with a CRF Model Based on Transformer Architecture

Author:

Al-Qurishi Muhammad,Souissi Riad,Al-Qaseemi Sarah

Publisher

Springer International Publishing

Reference42 articles.

1. Abdelali, A., Darwish, K., Durrani, N., Mubarak, H.: Farasa: A fast and furious segmenter for Arabic. In: Proceedings of the 2016 Conference of the North American Chapter of the Association for Computational Linguistics: Demonstrations, pp. 11–16 (2016)

2. AbdelRahman, S., Elarnaoty, M., Magdy, M., Fahmy, A.: Integrated machine learning techniques for Arabic named entity recognition. IJCSI 7(4), 27–36 (2010)

3. Abdul-Mageed, M., Elmadany, A., Nagoudi, E.M.B.: Arbert & MARBERT: deep bidirectional transformers for Arabic. Preprint (2020). arXiv:2101.01785

4. Aboaoga, M., Ab Aziz, M.J.: Arabic person names recognition by using a rule based approach. J. Comput. Sci. 9(7), 922 (2013)

5. Al-Qurishi, M.S., Souissi, R.: Arabic named entity recognition using transformer-based-crf model. In: Proceedings of The Fourth International Conference on Natural Language and Speech Processing (ICNLSP 2021), pp. 262–271 (2021)

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