@inproceedings{el-khbir-etal-2022-arabie,
    title = "{A}rab{IE}: Joint Entity, Relation and Event Extraction for {A}rabic",
    author = "El Khbir, Niama  and
      Tomeh, Nadi  and
      Charnois, Thierry",
    editor = "Bouamor, Houda  and
      Al-Khalifa, Hend  and
      Darwish, Kareem  and
      Rambow, Owen  and
      Bougares, Fethi  and
      Abdelali, Ahmed  and
      Tomeh, Nadi  and
      Khalifa, Salam  and
      Zaghouani, Wajdi",
    booktitle = "Proceedings of the Seventh Arabic Natural Language Processing Workshop (WANLP)",
    month = dec,
    year = "2022",
    address = "Abu Dhabi, United Arab Emirates (Hybrid)",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/jlcl-multiple-ingestion/2022.wanlp-1.31/",
    doi = "10.18653/v1/2022.wanlp-1.31",
    pages = "331--345",
    abstract = "Previous work on Arabic information extraction has mainly focused on named entity recognition and very little work has been done on Arabic relation extraction and event recognition. Moreover, modeling Arabic data for such tasks is not straightforward because of the morphological richness and idiosyncrasies of the Arabic language. We propose in this article the first neural joint information extraction system for the Arabic language."
}