Abstract
Word meaning is notoriously difficult to capture, both synchronically and diachronically. In this paper, we describe the creation of the largest resource of graded contextualized, diachronic word meaning annotation in four different languages, based on 100,000 human semantic proximity judgments. We describe in detail the multi-round incremental annotation process, the choice for a clustering algorithm to group usages into senses, and possible - diachronic and synchronic - uses for this dataset.
Cite
CITATION STYLE
Schlechtweg, D., Tahmasebi, N., Hengchen, S., Dubossarsky, H., & McGillivray, B. (2021). DWUG: A large Resource of Diachronic Word Usage Graphs in Four Languages. In EMNLP 2021 - 2021 Conference on Empirical Methods in Natural Language Processing, Proceedings (pp. 7079–7091). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/2021.emnlp-main.567
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