@inproceedings{aljabari-etal-2025-wojoodrelations,
    title = "$\mathrm{Wojood^{Relations}}$: {A}rabic Relation Extraction Corpus and Modeling",
    author = "Aljabari, Alaa  and
      Khalilia, Mohammed  and
      Jarrar, Mustafa",
    editor = "Christodoulopoulos, Christos  and
      Chakraborty, Tanmoy  and
      Rose, Carolyn  and
      Peng, Violet",
    booktitle = "Proceedings of the 2025 Conference on Empirical Methods in Natural Language Processing",
    month = nov,
    year = "2025",
    address = "Suzhou, China",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/ingest-emnlp/2025.emnlp-main.1741/",
    pages = "34330--34348",
    ISBN = "979-8-89176-332-6",
    abstract = "Relation extraction (RE) is a core task in natural language processing, crucial for semantic understanding, knowledge graph construction, and enhancing downstream applications. Existing work on Arabic RE remains limited due to the language{'}s rich morphology and syntactic complexity, and the lack of large, high-quality datasets. In this paper, we present $\mathrm{Wojood^{Relations}}$, the largest and most diverse Arabic RE corpus to date, containing over $33K$ sentences ($\sim550K$ tokens) annotated with $\sim15K$ relation triples across 40 relation types. The corpus is built on top of Wojood NER dataset with manual relation annotations carried out by expert annotators, achieving a Cohen{'}s $\kappa$ of 0.92, indicating high reliability. In addition, we propose two methods: NLI-RE, which formulates RE as a binary natural language inference problem using relation-aware templates, and GPT-Joint, a few-shot LLM framework for joint entity and RE via relation-aware retrieval. Finally, we benchmark the dataset using both supervised models and in-context learning with LLMs. Supervised models achieve 92.89{\%} F1 for RE, while LLMs obtain 72.73{\%} F1 for joint entity and RE. These results establish strong baselines, highlight key challenges, and provide a foundation for advancing Arabic RE research."
}