Abstract
This paper proposes an approach to classify definitions as they appear in popularizing texts. Following the function theory of lexicography, we propose a user-centered classification that breaks down definitions according to the way they are deployed in the text and the information they encode. We hypothesize that different types of users can benefit from this classification, which covers a range of definitional styles, from the classic genus et differentia model to function-oriented definitions. The corpus used for this task consists of 50 transcripts from The Science Magazine Podcast (around 400k words), where 570 snippets containing definitional information have been manually annotated and classified.
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