CORPORA-BASED ANALYSIS OF SPECIALISED TEXTS FOR TRANSLATION TRAINING: TERMS AND NEOLOGISMS
DOI:
https://doi.org/10.32782/2522-4077-2025-213-23Keywords:
corpus-based research, corpus, professional text, core vocabulary, term, neologism, Sketch Engine, CQL universal query languageAbstract
Language corpora are one of the most effective tools of applied linguistics, which are actively used in various fields of human life. The automated selection, compilation and analysis of text corpora of virtually unlimited size open up new perspectives not only for linguistic research, but also for professionals who use such data to solve practical problems. Corpus-based methods have great potential for improving language teaching, including translation, as they allow for the accurate and targeted selection of specialised linguistic materials necessary for mastering the lexical minimum, peculiarities of usage and translation of key language units, as well as for identifying current language trends in a particular field.Among the tools for working with corpora, Sketch Engine stands out as one of the most powerful, as it does not only analyse existing corpora but also creates your own, including multilingual ones. This makes it possible to quickly and efficiently research professional texts, identify key terminology and common phrases, analyse translation strategies, and create training materials for future translators. The use of the CQL query language allows improving search accuracy and obtaining more relevant linguistic data.The given article, which is a part of a larger study, discusses such an important function of Sketch Engine for searching, analysing and selecting lexical material as term recognition and extraction using the built-in Sketch Engine Keywords tool. This tool not only allows to identify terms and term combinations in professional texts with high accuracy, but also to compare the frequency of use of such words and combinations in both the studied and the reference corpora, which significantly increases the efficiency of search in general and linguistic analysis of selected units in particular. Another aspect of this study is the methodology of corpus search for neologisms and rarely used words. The latter is a challenge for corpus-based text analysis, as there are no universal search formulas or even principles for finding such vocabulary, which, however, is an important component of professional texts.The study is based on a corpus of English-language legal texts related to the IT sector, including licence agreements and contracts.
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