Abstract
The task of Diachronic Word Sense Induction (DWSI) aims to identify the meaning of words from their context, taking the temporal dimension into account. In this paper we propose an evaluation method based on large-scale time-stamped annotated biomedical data, and a range of evaluation measures suited to the task. The approach is applied to two recent DWSI systems, thus demonstrating its relevance and providing an in-depth analysis of the models.- Anthology ID:
- 2020.findings-emnlp.284
- Volume:
- Findings of the Association for Computational Linguistics: EMNLP 2020
- Month:
- November
- Year:
- 2020
- Address:
- Online
- Editors:
- Trevor Cohn, Yulan He, Yang Liu
- Venue:
- Findings
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 3171–3180
- Language:
- URL:
- https://aclanthology.org/2020.findings-emnlp.284
- DOI:
- 10.18653/v1/2020.findings-emnlp.284
- Cite (ACL):
- Ashjan Alsulaimani, Erwan Moreau, and Carl Vogel. 2020. An Evaluation Method for Diachronic Word Sense Induction. In Findings of the Association for Computational Linguistics: EMNLP 2020, pages 3171–3180, Online. Association for Computational Linguistics.
- Cite (Informal):
- An Evaluation Method for Diachronic Word Sense Induction (Alsulaimani et al., Findings 2020)
- PDF:
- https://preview.aclanthology.org/emnlp-22-attachments/2020.findings-emnlp.284.pdf
- Code
- ashjanalsulaimani/dwsi-eval