aiqbench analysis
ArabiGEE introduces a structured, hierarchical taxonomy for Arabic grammatical error explanation that moves beyond free-form text generation to explicitly categorize errors across orthographic, morphological, syntactic, and lexical dimensions. By providing a standardized framework with 27 error types and 324 associated explanations, this resource enables more rigorous automatic evaluation of large language models on Arabic text correction tasks. The publicly available code and annotated corpora offer a concrete foundation for improving model interpretability and benchmarking in low-resource language settings.
ArabiGEE: A Hierarchical Taxonomy for Arabic Grammatical Error Explanation
arXiv:2606.10765v1 Announce Type: new Abstract: We introduce ArabiGEE, the first comprehensive Arabic grammatical error explanation (GEE) taxonomy grounded in explicit error types. Unlike existing GEE approaches that treat explanation generation as free-form text, ArabiGEE organizes grammatical explanations through a hierarchical structure spanning orthographic, morphological, syntactic, and lexical dimensions. The taxonomy consists of 27 error types, 140 correction types, and 324 associated explanations. We apply ArabiGEE to manually annotate portions of existing Arabic grammatical error correction corpora and demonstrate how structured grammatical explanations can support automatic evaluation of LLMs on Arabic GEE. Our code and data are publicly available.
Abstract:We introduce ArabiGEE, the first comprehensive Arabic grammatical error explanation (GEE) taxonomy grounded in explicit error types. Unlike existing GEE approaches that treat explanation generation as free-form text, ArabiGEE organizes grammatical explanations through a hierarchical structure spanning orthographic, morphological, syntactic, and lexical dimensions. The taxonomy consists of 27 error types, 140 correction types, and 324 associated explanations. We apply ArabiGEE to manually annotate portions of existing Arabic grammatical error correction corpora and demonstrate how structured grammatical explanations can support automatic evaluation of LLMs on Arabic GEE. Our code and data are publicly available.
Computation and Language (cs.CL)
arXiv:2606.10765 [cs.CL]
(or arXiv:2606.10765v1 [cs.CL] for this version)
https://doi.org/10.48550/arXiv.2606.10765 Focus to learn more arXiv-issued DOI via DataCite (pending registration)
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