Abstract
We propose a solution for the LSCDiscovery shared task on Lexical Semantic Change Detection in Spanish. Our approach is based on generating lexical substitutes that describe old and new senses of a given word. This approach achieves the second best result in sense loss and sense gain detection subtasks. By observing those substitutes that are specific for only one time period, one can understand which senses were obtained or lost. This allows providing more detailed information about semantic change to the user and makes our method interpretable.- Anthology ID:
- 2022.lchange-1.17
- Volume:
- Proceedings of the 3rd Workshop on Computational Approaches to Historical Language Change
- Month:
- May
- Year:
- 2022
- Address:
- Dublin, Ireland
- Editors:
- Nina Tahmasebi, Syrielle Montariol, Andrey Kutuzov, Simon Hengchen, Haim Dubossarsky, Lars Borin
- Venue:
- LChange
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 165–172
- Language:
- URL:
- https://aclanthology.org/2022.lchange-1.17
- DOI:
- 10.18653/v1/2022.lchange-1.17
- Cite (ACL):
- Artem Kudisov and Nikolay Arefyev. 2022. BOS at LSCDiscovery: Lexical Substitution for Interpretable Lexical Semantic Change Detection. In Proceedings of the 3rd Workshop on Computational Approaches to Historical Language Change, pages 165–172, Dublin, Ireland. Association for Computational Linguistics.
- Cite (Informal):
- BOS at LSCDiscovery: Lexical Substitution for Interpretable Lexical Semantic Change Detection (Kudisov & Arefyev, LChange 2022)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-3/2022.lchange-1.17.pdf