@inproceedings{cassotti-etal-2024-using,
title = "Using Synchronic Definitions and Semantic Relations to Classify Semantic Change Types",
author = "Cassotti, Pierluigi and
De Pascale, Stefano and
Tahmasebi, Nina",
editor = "Ku, Lun-Wei and
Martins, Andre and
Srikumar, Vivek",
booktitle = "Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
month = aug,
year = "2024",
address = "Bangkok, Thailand",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.acl-long.249",
pages = "4539--4553",
abstract = "There is abundant evidence of the fact that the way words change their meaning can be classified in different types of change, highlighting the relationship between the old and new meanings (among which generalisation, specialisation and co-hyponymy transfer).In this paper, we present a way of detecting these types of change by constructing a model that leverages information both from synchronic lexical relations and definitions of word meanings. Specifically, we use synset definitions and hierarchy information from WordNet and test it on a digitized version of Blank{'}s (1997) dataset of semantic change types. Finally, we show how the sense relationships can improve models for both approximation of human judgments of semantic relatedness as well as binary Lexical Semantic Change Detection.",
}
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<abstract>There is abundant evidence of the fact that the way words change their meaning can be classified in different types of change, highlighting the relationship between the old and new meanings (among which generalisation, specialisation and co-hyponymy transfer).In this paper, we present a way of detecting these types of change by constructing a model that leverages information both from synchronic lexical relations and definitions of word meanings. Specifically, we use synset definitions and hierarchy information from WordNet and test it on a digitized version of Blank’s (1997) dataset of semantic change types. Finally, we show how the sense relationships can improve models for both approximation of human judgments of semantic relatedness as well as binary Lexical Semantic Change Detection.</abstract>
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%0 Conference Proceedings
%T Using Synchronic Definitions and Semantic Relations to Classify Semantic Change Types
%A Cassotti, Pierluigi
%A De Pascale, Stefano
%A Tahmasebi, Nina
%Y Ku, Lun-Wei
%Y Martins, Andre
%Y Srikumar, Vivek
%S Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
%D 2024
%8 August
%I Association for Computational Linguistics
%C Bangkok, Thailand
%F cassotti-etal-2024-using
%X There is abundant evidence of the fact that the way words change their meaning can be classified in different types of change, highlighting the relationship between the old and new meanings (among which generalisation, specialisation and co-hyponymy transfer).In this paper, we present a way of detecting these types of change by constructing a model that leverages information both from synchronic lexical relations and definitions of word meanings. Specifically, we use synset definitions and hierarchy information from WordNet and test it on a digitized version of Blank’s (1997) dataset of semantic change types. Finally, we show how the sense relationships can improve models for both approximation of human judgments of semantic relatedness as well as binary Lexical Semantic Change Detection.
%U https://aclanthology.org/2024.acl-long.249
%P 4539-4553
Markdown (Informal)
[Using Synchronic Definitions and Semantic Relations to Classify Semantic Change Types](https://aclanthology.org/2024.acl-long.249) (Cassotti et al., ACL 2024)
ACL