@inproceedings{habash-etal-2025-guidelines,
    title = "Guidelines for Fine-grained Sentence-level {A}rabic Readability Annotation",
    author = "Habash, Nizar  and
      Taha-Thomure, Hanada  and
      Elmadani, Khalid  and
      Zeino, Zeina  and
      Abushmaes, Abdallah",
    editor = "Peng, Siyao  and
      Rehbein, Ines",
    booktitle = "Proceedings of the 19th Linguistic Annotation Workshop (LAW-XIX-2025)",
    month = jul,
    year = "2025",
    address = "Vienna, Austria",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/landing_page/2025.law-1.30/",
    pages = "359--376",
    ISBN = "979-8-89176-262-6",
    abstract = "This paper presents the annotation guidelines of the Balanced Arabic Readability Evaluation Corpus (BAREC), a large-scale resource for fine-grained sentence-level readability assessment in Arabic. BAREC includes 69,441 sentences (1M+ words) labeled across 19 levels, from kindergarten to postgraduate. Based on the Taha/Arabi21 framework, the guidelines were refined through iterative training with native Arabic-speaking educators. We highlight key linguistic, pedagogical, and cognitive factors in determining readability and report high inter-annotator agreement: Quadratic Weighted Kappa 81.8{\%} (substantial/excellent agreement) in the last annotation phase. We also benchmark automatic readability models across multiple classification granularities (19-, 7-, 5-, and 3-level). The corpus and guidelines are publicly available: http://barec.camel-lab.com."
}