@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://preview.aclanthology.org/jlcl-multiple-ingestion/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{\%}."
}