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ChainNet: Structured Metaphor and Metonymy in WordNet
Conference proceeding

ChainNet: Structured Metaphor and Metonymy in WordNet

Rowan Hall Maudslay, Simone Teufel, Francis Bond and James Pustejovsky
PROCEEDINGS OF THE 2024 JOINT INTERNATIONAL CONFERENCE ON COMPUTATIONAL LINGUISTICS, LANGUAGE RESOURCES AND EVALUATION, LREC-COLING 2024, pp.2984-2996
International Conference on Computational Linguistics Language Resources and Evaluation
01/01/2024
Handle:
https://hdl.handle.net/10192/79006

Abstract

Computer Science Computer Science, Artificial Intelligence Computer Science, Interdisciplinary Applications Language & Linguistics Linguistics Science & Technology Social Sciences Technology
The senses of a word exhibit rich internal structure. In a typical lexicon, this structure is overlooked: a word's senses are encoded as a list without inter-sense relations. We present ChainNet, a lexical resource which for the first time explicitly identifies these structures. ChainNet expresses how senses in the Open English Wordnet are derived from one another: every nominal sense of a word is either connected to another sense by metaphor or metonymy, or is disconnected in the case of homonymy. Because WordNet senses are linked to resources which capture information about their meaning, ChainNet represents the first dataset of grounded metaphor and metonymy.

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