Algorithms based on quantum physics can help model processes related to the composition of lexical semantic units given the meaning of a word. This includes modeling term dependencies and modeling grammar

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Both quantum-inspired algorithms and quantum algorithms can model different features in the language; these are broken down into word representation and composition

Modeling Targets of Quantum NLP

Natural Language Processing Meets Quantum Physics: A Survey and Categorization(https://aclanthology.org/2021.emnlp-main.254) (Wu et al., EMNLP 2021)

Natural Language Processing Meets Quantum Physics: A Survey and Categorization (Wu et al.)

Using quantum physics for word representation has the potential to help including more features for words; more specifically, quantum/quantum-inspired algorithms can better help model word ambiguity and hyponymy relations

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