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    Lexikos

    versão On-line ISSN 2224-0039
    versão impressa ISSN 1684-4904

    Resumo

    PTASZNIK, Bartosz. Which Defining Model Contributes to More Successful Extraction of Syntactic Class Information and Translation Accuracy?. Lexikos [online]. 2020, vol.30, pp.1-23. ISSN 2224-0039.  http://dx.doi.org/10.5788/30-1-1545.

    Definitions in English monolingual learners' dictionaries are the central focus of the paper. Metalexicographers have had a consuming interest in the following three types of definitions: analytical definitions (or classical definitions), full-sentence definitions (also called contextual definitions) and single-clause when-definitions. The use of when-definitions, the role of which is to define abstract nouns, has raised questions and doubts as to their efficacy on correct part of speech recognition of the definiendum, or item being defined, in light of the problems related to the substi-tutability of headwords and parts of definitions (lack of general category words in this definition format). By and large, existing research has substantiated the superiority of the classical definition-type over single-clause when-definitions with respect to the accuracy of word class identification. The current experiment attempts to further delve into the subject of part of speech recognition with regard to the three aforementioned defining formats - in previous studies only data from analytical and single-clause when-definitions were collated, since contextual definitions were not included in the study design. The study was conducted on a group of 120 advanced-level Polish university students of English. The subjects were tested on their ability of correct extraction of syntactic class information and translation accuracy of abstract noun headwords as regards the three predominant definition-types in English lexicographic practice.

    Palavras-chave : Learners' Dictionaries; Definitions; Monolingual Dictionaries; Analytical Definitions; Full-sentence Definitions; Single-clause When-definitions.

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