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[ARTICLE · art-155030] src=arxiv.org ↗ pub= topic=natural-language-processing verified=true sentiment=↑ positive

A Parallel Multi-Dialect Arabic Dependency Treebank

Researchers released MADARTB, described as the first large-scale parallel dependency treebank for Arabic dialects, covering five city dialects — Beirut, Cairo, Doha, Rabat and Tunis — plus an extended Modern Standard Arabic version, totaling 5,000 sentences annotated under the CATiB dependency scheme. In a cross-dialect parsing comparison, a supervised parser reached 87.5% labeled attachment score (LAS) while the best of four LLM setups trailed at 85.7% LAS across all six varieties on the test set. The authors report that global construction profiles are highly similar across varieties but local syntactic structures frequently diverge, and they released the annotations and models publicly.

by read1 min views1 publishedOct 22, 2026

arXiv:2610.28823v1 Announce Type: new Abstract: Dependency parsing resource development for Arabic has largely focused on Modern Standard Arabic, leaving dialectal Arabic comparatively under-resourced. We introduce MADARTB, the first large-scale parallel dependency treebank spanning five city dialects: Beirut, Cairo, Doha, Rabat and Tunis, and extending an existing parallel MSA version. In total MADARTB consists of 5,000 sentences annotated using the CATiB dependency scheme. We analyze syntactic similarity across all city dialects and MSA. Although global construction profiles exhibit high similarity across varieties, local syntactic structures frequently diverge, revealing substantial structural variation across dialects. We further establish a cross-dialect dependency parsing comparison using a supervised parser and four LLMs. The supervised parser achieves 87.5% LAS, while the best LLM setup trails at 85.7% LAS across all six varieties on the test set. We release our annotations and models publicly.

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