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Abstrakt
This study explores the interface between syntax and semantics by examining the distribution of thematic roles across different text genres through computational means in the context of translation as a form of linguistic mediation. The research sets out to evaluate the accuracy of mapping syntactic categories (in particular those of subject and object) onto semantic roles of Agent and Patient using Natural Language Processing (NLP) approaches such as named entity recognition, CQL query and machine learning. The analysis is conducted across three distinct corpus samples: legal discourse, literature, and media publications. The results point to the very complex, non-isomorphic nature of the syntax-semantics interface, which may be interpreted as indicative of the application of deliberate mediatory techniques aiming to achieve a desired level of hybridity in the translated text.
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