EDRAC: 4,977 QA Pairs Expose Dialect Gaps in Arabic Reading Comprehension
preslav_nakov · x · 2026-10-26
An EMNLP 2026 Findings paper introduces EDRAC, the first large-scale benchmark for dialectal Arabic machine reading comprehension and generative QA.
- Covers 5 major dialects (Egyptian, Moroccan, Emirati, Syrian, Saudi) with 499 passages from natural spoken interactions and 4,977 QA pairs, built via a human–LLM collaborative pipeline with iterative generation, LLM-as-a-judge, and human verification.
- Evaluations of Arabic-centric and multilingual LLMs reveal substantial gaps between semantic answer quality and dialectal fidelity — high BERTScore (e.g., 81 for UAE dialect) can hide very low human-rated dialectal naturalness.
Conclusion: EDRAC offers a realistic, challenging benchmark for dialectal Arabic NLP and highlights limits of current evaluation metrics.
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