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.- Anthology ID:
- 2024.acl-long.249
- Volume:
- Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)
- Month:
- August
- Year:
- 2024
- Address:
- Bangkok, Thailand
- Editors:
- Lun-Wei Ku, Andre Martins, Vivek Srikumar
- Venue:
- ACL
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 4539–4553
- Language:
- URL:
- https://aclanthology.org/2024.acl-long.249
- DOI:
- Cite (ACL):
- Pierluigi Cassotti, Stefano De Pascale, and Nina Tahmasebi. 2024. Using Synchronic Definitions and Semantic Relations to Classify Semantic Change Types. In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), pages 4539–4553, Bangkok, Thailand. Association for Computational Linguistics.
- Cite (Informal):
- Using Synchronic Definitions and Semantic Relations to Classify Semantic Change Types (Cassotti et al., ACL 2024)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2024.acl-long.249.pdf