SOURCE-LINKED INTELLIGENCE
Scaling Hindi Quantum Natural Language Processing through Automatic Pregroup Supertagging
Quantum Natural Language Processing (QNLP) uses pregroup grammars to translate grammatical structure into diagrammatic representations and quantum circuits. Recent Hindi QNLP work has shown that Hindi-specific pregroup grammars can support grammar-sensitive compositional models, but grammatical type assignment is still largely manual, limiting scalability. This paper formulates automatic Hindi pregroup supertagging as a token-level classification task. Using a manually annotated corpus of 380 Hindi sentences, we evaluate lexical, contextual, prompting-based, lexical-repair, and suffix/morpholo
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Evidence & attribution
- arXiv · AI, language, vision and robotics · 2026-09-12T05:13:45.000Z
First collected: 2026-09-20T16:41:15.630Z. This is not the publication date.