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Quantum Compositional NLP for Arabic: Grammar, Morphology, and Word Sense in Circuit Topology

Researchers present the first application of pregroup grammar-based quantum compositional natural language processing (QNLP) to Arabic, converting sentences into quantum circuits that mirror grammatical structure. In three controlled experiments spanning word order, morphological tense, and verb sense disambiguation, the quantum circuit methods are compared against classical baselines including AraVec and AraBERT.

read1 min views25 publishedJul 17, 2026

arXiv:2607.14100v1 Announce Type: new Abstract: We present the first application of pregroup grammar-based quantum compositional natural language processing (QNLP) to Arabic; a morphologically rich, free-word-order language whose structural complexity provides a uniquely demanding testbed for theories of meaning composition in quantum circuits. Our system converts Arabic sentences into quantum circuits whose topology mirrors grammatical structure: subjects, verbs, and objects become quantum gates, and the typed dependencies between them (the pregroup grammar) determine how those gates are wired together. We conduct three controlled experiments spanning word order, morphological tense, and verb sense disambiguation, comparing quantum circuit methods against classical baselines including AraVec (Arabic word embeddings) and AraBERT (a pre-trained Arabic transformer).

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