{"url":"/dataset/geneutral","name":"GENEUTRAL","full_name":null,"description_markdown":"# Dataset Card for Dataset Name\r\n\r\n<!-- Provide a quick summary of the dataset. -->\r\n\r\nThis dataset is a filtered version of [BookCorpus](https://huggingface.co/datasets/bookcorpus/bookcorpus) containing only gender-neutral words.\r\n\r\n```python\r\ngeneutral = load_dataset('aieng-lab/geneutral', trust_remote_code=True, split='train')\r\n```\r\n\r\n## Examples:\r\n\r\nIndex | Text\r\n------|-----\r\n8498  | no one sitting near me could tell that i was seething with rage .\r\n8500  | by now everyone knew we were an item , the thirty-five year old business mogul , and the twenty -three year old pop sensation .\r\n8501  | we 'd been able to keep our affair hidden for all of two months and that only because of my high security .\r\n8503  | i was n't too worried about it , i just do n't like my personal life splashed across the headlines , but i guess it came with the territory .\r\n8507  | i 'd sat there prepared to be bored out of my mind for the next two hours or so .\r\n8508  | i 've seen and had my fair share of models over the years , and they no longer appealed .\r\n8512  | when i finally looked up at the stage , my breath had got caught in my lungs .\r\n8516  | i pulled my phone and cancelled my dinner date and essentially ended the six-month relationship i 'd been barely having with another woman .\r\n8518  | when i see something that i want , i go after it .\r\n8529  | if i had anything to say about that , it would be a permanent thing , or until i 'd had my fill at least .\r\n\r\n\r\n## Dataset Details\r\n\r\n<!-- Provide the basic links for the dataset. -->\r\n\r\n- **Repository:** [github.com/aieng-lab/gradiend](https://github.com/aieng-lab/gradiend)\r\n- **Original Data**: [BookCorpus](https://huggingface.co/datasets/bookcorpus/bookcorpus)\r\n\r\n> **__NOTE:__** This dataset is derived from BookCorpus, for which we do not have publication rights. Therefore, this repository only provides indices referring to gender-neutral entries within the BookCorpus dataset on Hugging Face. By using `load_dataset('aieng-lab/geneutral', trust_remote_code=True, split='train')`, both the indices and the full BookCorpus dataset are downloaded locally. The indices are then used to construct the GENEUTRAL dataset. The initial dataset generation takes a few minutes, but subsequent loads are cached for faster access.\r\n\r\n## Uses\r\n\r\n<!-- Address questions around how the dataset is intended to be used. -->\r\n\r\nThis dataset is suitable for training and evaluating language models. For example, its lack of gender-related words makes it ideal for assessing language modeling capabilities in both gender-biased and gender-neutral models during masked language modeling (MLM) tasks, allowing for an evaluation independent of gender bias.\r\n\r\n\r\n## Dataset Creation\r\n\r\nWe generated this dataset by filtering the BookCorpus dataset, leaving only entries matching the following criteria:\r\n- Each entry contains at least 50 characters\r\n- No name of [aieng-lab/namextend](https://huggingface.co/datasets/aieng-lab/geneutral)\r\n- No gender-specific pronoun is contained (he/she/him/her/his/hers/himself/herself)\r\n- No gender-specific noun is contained according to the 2421 plural-extended entries of this [gendered-word dataset](https://github.com/ecmonsen/gendered_words)","description_withheld":null,"homepage":"https://huggingface.co/datasets/aieng-lab/geneutral","introduced_date":"2025-02-03","introduced_date_note":null,"introduced_by":{"paper":"/paper/gradiend-monosemantic-feature-learning-within","title":"GRADIEND: Monosemantic Feature Learning within Neural Networks Applied to Gender Debiasing of Transformer Models","first_author":"Jonathan Drechsel","url":null},"license":{"name":"cc-by-4.0","url":null},"modalities":[{"name":"Texts","url":"/datasets/modality/texts"}],"tasks":[{"name":"Masked Language Modeling","url":"/task/masked-language-modeling","datasets_with_task":"/datasets/task/masked-language-modeling"}],"languages":[{"name":"English","url":"/datasets/language/english"}],"variants":["GENEUTRAL"],"data_loaders":[],"num_papers_in_archive":1,"source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28"},"benchmarks":[],"papers_with_a_benchmark_row":[],"syntology_totals":{"read_at":"2026-09-24T18:15:14+00:00","papers_with_samples":0,"samples_harvested":0,"samples_ran":0,"samples_unverified":0,"pointer_only_for_licence":0,"papers_with_no_sample_that_ran":0,"note":"the per-paper counts above, summed; not a rate"},"papers_note":"The archive never published its papers-using-dataset list; these are papers with a leaderboard row on this dataset's benchmarks."}