@inproceedings{eb41752e2f6547a5bde493bbb467f934,
title = "ChiWUG: A Graph-based Evaluation Dataset for Chinese Lexical Semantic Change Detection",
abstract = "Recent studies suggested that language models are efficient tools for measuring lexical semantic change. In our paper, we present the compilation of the first graph-based evaluation dataset for semantic change in the context of the Chinese language, covering the periods before and after the Reform and Opening Up. Exploiting the existing framework DURel, we collect over 61,000 human semantic relatedness judgments for 40 targets. The inferred word usage graphs and semantic change scores provide a basis for visualization and evaluation of semantic change.",
author = "Jing Chen and Emmanuele Chersoni and Dominik Schlechtweg and Jelena Prokic and Huang, {Chu Ren}",
note = "Publisher Copyright: {\textcopyright} 2023 Association for Computational Linguistics.; 4th International Workshop on Computational Approaches to Historical Language Change, LChange 2023 ; Conference date: 06-12-2023",
year = "2023",
month = dec,
day = "6",
language = "English",
series = "LChange 2023 - 4th International Workshop on Computational Approaches to Historical Language Change 2023, Proceedings",
publisher = "Association for Computational Linguistics (ACL)",
pages = "93--99",
editor = "Nina Tahmasebi and Syrielle Montariol and Haim Dubossarsky and Haim Dubossarsky and Andrey Kutuzov and Simon Hengchen and David Alfter and Francesco Periti and Pierluigi Cassotti",
booktitle = "LChange 2023 - 4th International Workshop on Computational Approaches to Historical Language Change 2023, Proceedings",
address = "United States",
}