The development of digital learning platforms, electronic document management systems, and web-based systems that process natural language text information has led to an increase in the volume of content and/or arrays of processed full-text documents. This, in turn, has increased the demand for highly effective natural language processing methods capable of capturing text semantics. This article proposes a hybrid architecture based on the integration of probabilistic and fuzzy logic that effectively addresses semantic ambiguity issues by integrating stochastic and fuzzy logic channels that take into account both statistical patterns and linguistic uncertainty.

Keywords: integration, semantics, interpretation, natural language, uncertainty, patterns