Understanding lexico-semantic opposition empty/full in official business texts: Quantitative and qualitative research

Authors

  • Demyanchuk Yuliya

    Foreign Languages and Translation Studies Department, Lviv State University of Life Safety

DOI:

https://doi.org/10.59400/fls.v6i1.2004

Abstract

This paper discusses the lexical-semantic opposition EMPTY/FULL in the corpus of legal, military and medical texts. The study analyzes 130 official business texts, in which we examined the problem of defining and constructing the lexical-semantic opposition EMPTY/FULL. The analysis promoted the construction of quantitative sampling, which demonstrates the weight of the lexemes in the corpus of official business texts. The purpose of the proposed analysis was to determine the distribution of the lexical-semantic opposition EMPTY/FULL, especially to find out the total number of occurrences, the average number of occurrences and the edge limits of the lexeme EMPTY and the lexeme FULL in the corpus of texts. The main results of the study outline the diversity of the lexical-semantic opposition EMPTY/FULL in different contexts, that underlines the functional diversification of the lexeme EMPTY and lexeme FULL. The results showed that in legal texts lexemes EMPTY/FULL nominate a legal concept; in medical texts they perform the function of medical conditions assessment; within the limits of military texts, they establish an associative connection between the nomination and semantic components (military actions, targets and objects of military use, consequences of war). Another important finding was the determination of the dominant lexeme in the corpus of legal texts and the dominant lexeme in the corpus of military texts. The similarities between EMPTY and FULL are primarily due to their antonymy. However, their differences are fixed in their distinct core meanings, contextual usage, pragmatic significance and connotations. These differences make them adaptable in various contexts of military, legal and medical texts to convey precise and often contrasting information about the state of objects and concepts.

Keywords:

lexical-semantic opposition EMPTY/FULL, official business texts, Python, corpus of texts, qualitative and quantitative research, military, legal and medical texts, Orange software

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Vol. 6 , Iss. 1 (March 2024)

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