@inproceedings{maudslay-etal-2024-chainnet,
title = "{C}hain{N}et: Structured Metaphor and Metonymy in {W}ord{N}et",
author = "Maudslay, Rowan Hall and
Teufel, Simone and
Bond, Francis and
Pustejovsky, James",
editor = "Calzolari, Nicoletta and
Kan, Min-Yen and
Hoste, Veronique and
Lenci, Alessandro and
Sakti, Sakriani and
Xue, Nianwen",
booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)",
month = may,
year = "2024",
address = "Torino, Italia",
publisher = "ELRA and ICCL",
url = "https://aclanthology.org/2024.lrec-main.266",
pages = "2984--2996",
abstract = "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, by expressing how senses in the Open English Wordnet are derived from one another. In ChainNet, 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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<abstract>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, by expressing how senses in the Open English Wordnet are derived from one another. In ChainNet, 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.</abstract>
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%0 Conference Proceedings
%T ChainNet: Structured Metaphor and Metonymy in WordNet
%A Maudslay, Rowan Hall
%A Teufel, Simone
%A Bond, Francis
%A Pustejovsky, James
%Y Calzolari, Nicoletta
%Y Kan, Min-Yen
%Y Hoste, Veronique
%Y Lenci, Alessandro
%Y Sakti, Sakriani
%Y Xue, Nianwen
%S Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
%D 2024
%8 May
%I ELRA and ICCL
%C Torino, Italia
%F maudslay-etal-2024-chainnet
%X 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, by expressing how senses in the Open English Wordnet are derived from one another. In ChainNet, 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.
%U https://aclanthology.org/2024.lrec-main.266
%P 2984-2996
Markdown (Informal)
[ChainNet: Structured Metaphor and Metonymy in WordNet](https://aclanthology.org/2024.lrec-main.266) (Maudslay et al., LREC-COLING 2024)
ACL
- Rowan Hall Maudslay, Simone Teufel, Francis Bond, and James Pustejovsky. 2024. ChainNet: Structured Metaphor and Metonymy in WordNet. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 2984–2996, Torino, Italia. ELRA and ICCL.