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tłumaczenie prawne
nauczanie przekładu.
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Abstrakt
W związku z poprawą jakości tłumaczenia maszynowego jest ono wykorzystywane przez adeptów sztuki przekładoznawczej w coraz to większym stopniu. Teksty prawne stanowią jednak spore wyzwanie dla przekładu maszynowego, prowadząc do rozważań nad możliwością wykorzystywania tłumaczenia maszynowego właśnie do pracy nad takimi tekstami jak i nad potencjalnym zastosowaniem w nauczaniu przekładu. W celu analizy tego zagadnienia, podjęto pracę nad systemem tłumaczenia maszynowego DeepL Translator oraz systemem CAT integrującym tłumaczenie maszynowe – MateCat. Badania z wykorzystaniem obu systemów przeprowadzane były w różnym czasie, bez określonych pamięci tłumaczeniowych dla danych tekstów prawnych, dając zarazem podstawy dla oceny wyników i uszeregowania rodzajów błędów. Ocena opierała się na określonych kryteriach: 1) zrozumienie i znaczenie tekstu docelowego; 2) relacja między tekstami wyjściowym a wejściowym w określonych sytuacjach tłumaczeniowych. Wyniki okazały się być niewystarczające do uznania za przydatne w postedycji tekstów prawnych w znacznym stopniu dla nauczania przekładu. Ocena relacji tekst wejściowy-wyjściowy była znacznie niższa niż ta dotycząca znaczenia tekstu, stąd postuluje się, że nauczanie przekładu powinno prowadzić do zwiększenia świadomości, że między rezultatem przekładem maszynowym a tłumaczeniem ludzkim występują różnice oraz usprawnień w obszarze kompetencji prawnych i prawniczych jak i w podejściu translatorskim.Bibliografia
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