Abstract
We observe an instance of gender-induced bias in a downstream application, despite the absence of explicit gender words in the test cases. We provide a test set, SoWinoBias, for the purpose of measuring such latent gender bias in coreference resolution systems. We evaluate the performance of current debiasing methods on the SoWinoBias test set, especially in reference to the method’s design and altered embedding space properties. See https://github.com/hillary-dawkins/SoWinoBias.- Anthology ID:
- 2021.gebnlp-1.12
- Volume:
- Proceedings of the 3rd Workshop on Gender Bias in Natural Language Processing
- Month:
- August
- Year:
- 2021
- Address:
- Online
- Editors:
- Marta Costa-jussa, Hila Gonen, Christian Hardmeier, Kellie Webster
- Venue:
- GeBNLP
- SIG:
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 103–111
- Language:
- URL:
- https://aclanthology.org/2021.gebnlp-1.12
- DOI:
- 10.18653/v1/2021.gebnlp-1.12
- Cite (ACL):
- Hillary Dawkins. 2021. Second Order WinoBias (SoWinoBias) Test Set for Latent Gender Bias Detection in Coreference Resolution. In Proceedings of the 3rd Workshop on Gender Bias in Natural Language Processing, pages 103–111, Online. Association for Computational Linguistics.
- Cite (Informal):
- Second Order WinoBias (SoWinoBias) Test Set for Latent Gender Bias Detection in Coreference Resolution (Dawkins, GeBNLP 2021)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/2021.gebnlp-1.12.pdf
- Data
- WinoBias