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--- |
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license: openrail |
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language: |
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- is |
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tags: |
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- bias-detection |
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- icelandic |
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- ner |
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- socially-responsible-ai |
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- prejudice-detection |
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- huggingface |
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- dataset |
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--- |
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# Icelandic Bias-Aware NER Dataset |
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**Trigger warning:** This dataset contains biased, offensive, or harmful language. Examples are included solely for research purposes. |
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## Dataset Description |
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This dataset contains Icelandic sentences annotated for biased and potentially harmful expressions across 14 categories. It was developed to support research in fairness-oriented NLP, especially for low-resource languages. |
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### Classes |
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- **B-ADDICTION, I-ADDICTION** |
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- **B-DISABILITY, I-DISABILITY** |
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- **B-ORIGIN, I-ORIGIN** |
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- **B-GENERAL, I-GENERAL** |
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- **B-LGBTQIA, I-LGBTQIA** |
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- **B-LOOKS, I-LOOKS** |
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- **B-PERSONAL, I-PERSONAL** |
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- **B-PROFANITY, I-PROFANITY** |
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- **B-RELIGION, I-RELIGION** |
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- **B-SEXUAL, I-SEXUAL** |
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- **B-SOCIAL_STATUS, I-SOCIAL_STATUS** |
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- **B-STUPIDITY, I-STUPIDITY** |
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- **B-VULGAR, I-VULGAR** |
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- **B-WOMEN, I-WOMEN** |
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Annotations follow the BIO scheme (e.g., `B-WOMEN`, `I-WOMEN`, `O`). |
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### Contents |
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- **all_balanced.txt**: 184,580 sentence examples created via weak supervision (lemmatized string matching against curated bias lexicon) |
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-**dev.txt**: A development dataset sampled from all_balanced.txt. It includes 15,381 sentence examples. |
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-**test.txt**: A testing dataset sampled from all_balanced.txt. It includes 15,383 sentence examples. |
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-**train.txt**: A training dataset sampled from all_balanced.txt. It includes 153,816 sentence examples |
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-**gold.txt** |
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**Automatically annotated set**: 15,383 sentences created via weak supervision (lemmatized string matching against curated bias lexicon) |
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- **Gold set**: 190 manually reviewed sentence examples from sources not included in the training, testing or development sets. |
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## Intended Uses & Limitations |
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### Intended Use |
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- Research on bias detection in Icelandic text |
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- Training and evaluation of bias-aware NLP models |
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- Educational purposes for raising awareness of bias in language |
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### Limitations |
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- Automatically annotated examples may include false positives and false negatives |
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- Vocabulary-based matching may miss subtle, euphemistic, or emerging forms of bias |
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- Gold set is relatively small |
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⚠ **Not intended for punitive monitoring or censorship.** Outputs are prompts for reflection, not judgments. |
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## Ethical Considerations |
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This dataset is released under the **[BigScience OpenRAIL-D License](https://www.licenses.ai/ai-licenses)**, which allows free use with responsible-use restrictions. |
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Prohibited uses include: |
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- Harassment or discrimination |
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- Generating disinformation or hateful content |
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- Surveillance targeting individuals or groups |
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The dataset includes harmful language and should be handled with care. Trigger warnings are recommended for any public deployment. |
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## Citation |
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Will be added. |
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