DWUG: A large Resource of Diachronic Word Usage Graphs in Four Languages
Dominik Schlechtweg, Nina Tahmasebi, Simon Hengchen, Haim Dubossarsky, Barbara McGillivray
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.- Anthology ID:
- 2021.emnlp-main.567
- Volume:
- Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing
- Month:
- November
- Year:
- 2021
- Address:
- Online and Punta Cana, Dominican Republic
- Editors:
- Marie-Francine Moens, Xuanjing Huang, Lucia Specia, Scott Wen-tau Yih
- Venue:
- EMNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 7079–7091
- Language:
- URL:
- https://aclanthology.org/2021.emnlp-main.567
- DOI:
- 10.18653/v1/2021.emnlp-main.567
- Cite (ACL):
- Dominik Schlechtweg, Nina Tahmasebi, Simon Hengchen, Haim Dubossarsky, and Barbara McGillivray. 2021. DWUG: A large Resource of Diachronic Word Usage Graphs in Four Languages. In Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing, pages 7079–7091, Online and Punta Cana, Dominican Republic. Association for Computational Linguistics.
- Cite (Informal):
- DWUG: A large Resource of Diachronic Word Usage Graphs in Four Languages (Schlechtweg et al., EMNLP 2021)
- PDF:
- https://preview.aclanthology.org/fix-volume-bibkeys/2021.emnlp-main.567.pdf