@inproceedings{laouirine-etal-2023-elyadata,
title = "{ELYADATA} at {W}ojood{NER} Shared Task: Data and Model-centric Approaches for {A}rabic Flat and Nested {NER}",
author = "Laouirine, Imen and
Elleuch, Haroun and
Bougares, Fethi",
editor = "Sawaf, Hassan and
El-Beltagy, Samhaa and
Zaghouani, Wajdi and
Magdy, Walid and
Abdelali, Ahmed and
Tomeh, Nadi and
Abu Farha, Ibrahim and
Habash, Nizar and
Khalifa, Salam and
Keleg, Amr and
Haddad, Hatem and
Zitouni, Imed and
Mrini, Khalil and
Almatham, Rawan",
booktitle = "Proceedings of ArabicNLP 2023",
month = dec,
year = "2023",
address = "Singapore (Hybrid)",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.arabicnlp-1.84",
doi = "10.18653/v1/2023.arabicnlp-1.84",
pages = "759--764",
abstract = "This paper describes our submissions to the WojoodNER shared task organized during the first ArabicNLP conference. We participated in the two proposed sub-tasks of flat and nested Named Entity Recognition (NER). Our systems were ranked first over eight and third over eleven in the Nested NER and Flat NER, respectively. All our primary submissions are based on DiffusionNER models (Shen et al., 2023), where the NER task is formulated as a boundary-denoising diffusion process. Experiments on nested WojoodNER achieves the best results with a micro F1-score of 93.73{\%}. For the flat sub-task, our primary system was the third-best system, with a micro F1-score of 91.92{\%}.",
}
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<abstract>This paper describes our submissions to the WojoodNER shared task organized during the first ArabicNLP conference. We participated in the two proposed sub-tasks of flat and nested Named Entity Recognition (NER). Our systems were ranked first over eight and third over eleven in the Nested NER and Flat NER, respectively. All our primary submissions are based on DiffusionNER models (Shen et al., 2023), where the NER task is formulated as a boundary-denoising diffusion process. Experiments on nested WojoodNER achieves the best results with a micro F1-score of 93.73%. For the flat sub-task, our primary system was the third-best system, with a micro F1-score of 91.92%.</abstract>
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%0 Conference Proceedings
%T ELYADATA at WojoodNER Shared Task: Data and Model-centric Approaches for Arabic Flat and Nested NER
%A Laouirine, Imen
%A Elleuch, Haroun
%A Bougares, Fethi
%Y Sawaf, Hassan
%Y El-Beltagy, Samhaa
%Y Zaghouani, Wajdi
%Y Magdy, Walid
%Y Abdelali, Ahmed
%Y Tomeh, Nadi
%Y Abu Farha, Ibrahim
%Y Habash, Nizar
%Y Khalifa, Salam
%Y Keleg, Amr
%Y Haddad, Hatem
%Y Zitouni, Imed
%Y Mrini, Khalil
%Y Almatham, Rawan
%S Proceedings of ArabicNLP 2023
%D 2023
%8 December
%I Association for Computational Linguistics
%C Singapore (Hybrid)
%F laouirine-etal-2023-elyadata
%X This paper describes our submissions to the WojoodNER shared task organized during the first ArabicNLP conference. We participated in the two proposed sub-tasks of flat and nested Named Entity Recognition (NER). Our systems were ranked first over eight and third over eleven in the Nested NER and Flat NER, respectively. All our primary submissions are based on DiffusionNER models (Shen et al., 2023), where the NER task is formulated as a boundary-denoising diffusion process. Experiments on nested WojoodNER achieves the best results with a micro F1-score of 93.73%. For the flat sub-task, our primary system was the third-best system, with a micro F1-score of 91.92%.
%R 10.18653/v1/2023.arabicnlp-1.84
%U https://aclanthology.org/2023.arabicnlp-1.84
%U https://doi.org/10.18653/v1/2023.arabicnlp-1.84
%P 759-764
Markdown (Informal)
[ELYADATA at WojoodNER Shared Task: Data and Model-centric Approaches for Arabic Flat and Nested NER](https://aclanthology.org/2023.arabicnlp-1.84) (Laouirine et al., ArabicNLP-WS 2023)
ACL