├── LICENSE ├── README.md └── data └── samples-1680.jsonl.gz /LICENSE: -------------------------------------------------------------------------------- 1 | MIT License 2 | 3 | Copyright (c) 2022 OpenAI 4 | 5 | Permission is hereby granted, free of charge, to any person obtaining a copy 6 | of this software and associated documentation files (the "Software"), to deal 7 | in the Software without restriction, including without limitation the rights 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 9 | copies of the Software, and to permit persons to whom the Software is 10 | furnished to do so, subject to the following conditions: 11 | 12 | The above copyright notice and this permission notice shall be included in all 13 | copies or substantial portions of the Software. 14 | 15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 21 | SOFTWARE. 22 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | ## Evaluation dataset for the paper "A Holistic Approach to Undesired Content Detection" 2 | 3 | The evaluation dataset `data/samples-1680.jsonl.gz` is the test set used in [the following paper](https://arxiv.org/abs/2208.03274): 4 | 5 | ``` 6 | @article{openai2022moderation, 7 | title={A Holistic Approach to Undesired Content Detection}, 8 | author={Todor Markov and Chong Zhang and Sandhini Agarwal and Tyna Eloundou and Teddy Lee and Steven Adler and Angela Jiang and Lilian Weng}, 9 | journal={arXiv preprint arXiv:2208.03274}, 10 | year={2022} 11 | } 12 | ``` 13 | 14 | Each line contains information about one sample in a JSON object and each sample is labeled according to our taxonomy. The category label is a binary flag, but if it does not include in the JSON, it means we do not know the label. 15 | 16 | | Category | Label | Definition | 17 | | -------- | ----- | ---------- | 18 | | sexual | `S` | Content meant to arouse sexual excitement, such as the description of sexual activity, or that promotes sexual services (excluding sex education and wellness). | 19 | | hate | `H` | Content that expresses, incites, or promotes hate based on race, gender, ethnicity, religion, nationality, sexual orientation, disability status, or caste. | 20 | | violence | `V` | Content that promotes or glorifies violence or celebrates the suffering or humiliation of others. | 21 | | harassment | `HR` | Content that may be used to torment or annoy individuals in real life, or make harassment more likely to occur. | 22 | | self-harm | `SH` | Content that promotes, encourages, or depicts acts of self-harm, such as suicide, cutting, and eating disorders. | 23 | | sexual/minors | `S3` | Sexual content that includes an individual who is under 18 years old. | 24 | | hate/threatening | `H2` | Hateful content that also includes violence or serious harm towards the targeted group. | 25 | | violence/graphic | `V2` | Violent content that depicts death, violence, or serious physical injury in extreme graphic detail. | 26 | 27 | -------------------------------------------------------------------------------- /data/samples-1680.jsonl.gz: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/openai/moderation-api-release/f4ab51b5edd3bfbcb349a56324274235b674e0e4/data/samples-1680.jsonl.gz --------------------------------------------------------------------------------