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Creation of intelligent systems in the paradigm of logical decision-making requires formalization of knowledge in the form of ontologies, production models, etc. However, a rigorous formalization of knowledge is far from always possible due to the incompleteness, inaccuracy, and inconsistency of the data. In this regard, recently, the attention of researchers has shifted to extracting knowledge from natural language texts. Particularly noteworthy is the recently developing approach based on the use of quantum formalism to the objects of the macrocosm, which allows one to consider the uncertainty and inaccuracy inherent in the natural language. Numerous experiments conducted over the past 30 years demonstrate that the mathematical apparatus developed for modeling elementary particles also satisfactorily describes the behavior of people, which cannot be described by the mathematical apparatus of classical logic and probability theory. A review of the methods of processing natural language texts by means of quantum mathematics is presented. The methods are designed to eliminate the shortcomings of existing methods and means of information retrieval.

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