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.
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.