Noor: A Pipeline Framework for Classical Arabic Parsing

Classical Arabic (CA) presents unique and significant challenges for computational syntactic analysis, primarily due to its complex morphosyntax, pervasive ellipsis, flexible word order, and the critical scarcity of comprehensive annotated resources. This paper introduces Noor, a novel multi-stage pipeline framework specifically engineered for robust, high-performance syntactic parsing of CA. The Noor framework integrates several key innovations: (1) a dedicated pre-parsing module (TAQDIR) employing a hybrid rule-based and heuristic approach for explicit ellipsis resolution; (2) parallel dependency (ARC-IIRAB) and constituency (ARC-MAHAL) parsers utilizing Bidirectional Long Short-Term Memory (BiLSTM)-based representations and tailored transition systems; and (3) a synthesis mechanism generating enriched hybrid syntactic representations. A primary contribution of this work is the creation and public release of the Quranic Treebank—the first complete, validated, and fully machine-readable hybrid syntactic resource for the CA, reconstructed and augmented using the Noor framework. Empirical evaluation demonstrates that Noor achieves state-of-the-art (SOTA) performance on CA parsing, with the hybrid parser significantly outperforming previous benchmarks by over 4.6 F1 points on the Extended Labeled Attachment Score (ELAS). The framework is complemented by IIRAB Vis, a novel visualization tool designed to render complex hybrid structures in alignment with traditional Arabic grammatical principles (I’rāb). By providing both a validated SOTA methodology and a foundational public dataset, this research substantially advances the computational analysis capabilities for CA across Natural Language Processing (NLP), digital humanities, and linguistic studies.