Lexicon of Changes: Towards the Evaluation of Diachronic Semantic Shift in Chinese

Jing Chen, Emmanuele Chersoni, Chu-ren Huang


Abstract
Recent research has brought a wind of using computational approaches to the classic topic of semantic change, aiming to tackle one of the most challenging issues in the evolution of human language. While several methods for detecting semantic change have been proposed, such studies are limited to a few languages, where evaluation datasets are available. This paper presents the first dataset for evaluating Chinese semantic change in contexts preceding and following the Reform and Opening-up, covering a 50-year period in Modern Chinese. Following the DURel framework, we collected 6,000 human judgments for the dataset. We also reported the performance of alignment-based word embedding models on this evaluation dataset, achieving high and significant correlation scores.
Anthology ID:
2022.lchange-1.11
Volume:
Proceedings of the 3rd Workshop on Computational Approaches to Historical Language Change
Month:
May
Year:
2022
Address:
Dublin, Ireland
Venue:
LChange
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
113–118
Language:
URL:
https://aclanthology.org/2022.lchange-1.11
DOI:
10.18653/v1/2022.lchange-1.11
Bibkey:
Cite (ACL):
Jing Chen, Emmanuele Chersoni, and Chu-ren Huang. 2022. Lexicon of Changes: Towards the Evaluation of Diachronic Semantic Shift in Chinese. In Proceedings of the 3rd Workshop on Computational Approaches to Historical Language Change, pages 113–118, Dublin, Ireland. Association for Computational Linguistics.
Cite (Informal):
Lexicon of Changes: Towards the Evaluation of Diachronic Semantic Shift in Chinese (Chen et al., LChange 2022)
Copy Citation:
PDF:
https://aclanthology.org/2022.lchange-1.11.pdf
Video:
 https://aclanthology.org/2022.lchange-1.11.mp4