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Guidelines for Fine-grained Sentence-level Arabic Readability Annotation

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arxiv 2410.08674 v3 pith:6NJPKTMT submitted 2024-10-11 cs.CL

classification cs.CL
keywords readabilityguidelinesannotationarabicacrossagreementbareccorpus
verification ladder T0 review T1 audit T2 compute T3 formal
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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.

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  1. Lemmatization as a Classification Task: Results from Arabic across Multiple Genres

    cs.CL 2025-06

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