FairForget/StereoSet-UK-Unlearning

StereoSet-UK Unlearning

StereoSet-UK Unlearning contains 2,101 Ukrainian full-sentence triplets derived from the intrasentence portion of the StereoSet development set. The Ukrainian sentences were translated with the DeepL API and received technical cleanup. English source text is omitted.

Each triplet assigns the stereotype sentence to forget_uk, the anti-stereotype sentence to retain_uk, and the unrelated sentence to control_uk. Five items with duplicate translated candidates were excluded.

The 79 source targets use unique, standardized Ukrainian labels. The labels are metadata values and are independent of grammatical inflections inside the full sentences.

The role assignment is an experimental unlearning view created for this release. StereoSet's original scope is stereotypical-bias evaluation. A separate retain corpus is still needed to preserve general language ability and factual knowledge.

Fields

Field	Description
item_id	Original StereoSet item identifier
bias_type_uk	Ukrainian bias-category label
target_uk	Canonical Ukrainian label for the bias target
forget_uk	Full Ukrainian stereotype sentence
retain_uk	Full Ukrainian anti-stereotype sentence
control_uk	Full Ukrainian unrelated sentence

This is a provisional machine-translated research dataset. Human validation is still required.

Ukrainian adaptation

The Ukrainian translation, cleaning, and adaptation were prepared by Viktoriia Makovska, Oleksandra Ostafiichuk, and Tetiana Zakharchenko.

Source and license

This dataset is derived from StereoSet at source commit ead7d086a64a192a1eca88e0dd2fd163de375218. The source and this translation use the Creative Commons Attribution-ShareAlike 4.0 International license.

Citation

Please cite both the Ukrainian adaptation and the original StereoSet paper.

Ukrainian adaptation

@dataset{makovska_etal_2026_stereoset_uk_unlearning,
  title = {{StereoSet-UK Unlearning}: Ukrainian Translation, Cleaning, and Adaptation for Machine Unlearning},
  author = {Makovska, Viktoriia and Ostafiichuk, Oleksandra and Zakharchenko, Tetiana},
  year = {2026},
  publisher = {FairForget},
  url = {https://huggingface.co/datasets/FairForget/StereoSet-UK-Unlearning}
}

Original StereoSet

@inproceedings{nadeem-etal-2021-stereoset,
  title = {{StereoSet}: Measuring stereotypical bias in pretrained language models},
  author = {Nadeem, Moin and Bethke, Anna and Reddy, Siva},
  booktitle = {Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing},
  year = {2021},
  pages = {5356--5371},
  doi = {10.18653/v1/2021.acl-long.416},
  url = {https://aclanthology.org/2021.acl-long.416/}
}