public_domain_review

# Public Domain Review ## Description The [Public Domain Review](http://publicdomainreview.org) is an online journal dedicated to exploration of works of art and literature that have aged into the public domain. We collect all articles published in the Public Domain Review under a CC BY-SA license. ## Dataset Statistics | Documents | UTF-8 GB | |-----------|----------| | 1,412 | 0.007 | ## License Issues While we aim to produce datasets with completely accurate licensing information, license laundering and inaccurate metadata can cause us to erroneously assign the incorrect license to some documents (for further discussion of this limitation, please see [our paper](https://huggingface.co/papers/2506.05209)). If you believe you have found an instance of incorrect licensing in this dataset, please [start a discussion](https://github.com/r-three/common-pile/discussions/new) on this repository. ## Other Versions This is the "raw" version of the Public Domain Review dataset. If you are looking for the filtered version used to train [Comma v0.1](https://huggingface.co/common-pile/comma-v0.1), you can find it [here](https://huggingface.co/datasets/common-pile/public_domain_review_filtered). ## Citation If you use this dataset, please cite: ```bibtex @article{kandpal2025common, title={{The Common Pile v0.1: An 8TB Dataset of Public Domain and Openly Licensed Text}}, author={Nikhil Kandpal and Brian Lester and Colin Raffel and Sebastian Majstorovic and Stella Biderman and Baber Abbasi and Luca Soldaini and Enrico Shippole and A. Feder Cooper and Aviya Skowron and Shayne Longpre and Lintang Sutawika and Alon Albalak and Zhenlin Xu and Guilherme Penedo and Loubna Ben and Elie Bakouch and John David and Honglu Fan and Dashiell Stander and Guangyu Song and Aaron Gokaslan and John Kirchenbauer and Tom Goldstein and Brian R and Bhavya Kailkhura and Tyler Murray}, journal={arXiv preprint}, year={2025} } ```# 公有领域评论（Public Domain Review） ## 概述 [公有领域评论（Public Domain Review）](http://publicdomainreview.org)是一家致力于探究已进入公有领域的艺术与文学作品的在线期刊。我们将该期刊发布的所有文章以CC BY-SA许可协议进行收录。 ## 数据集统计信息 | 文档数量 | UTF-8 吉字节 | |-----------|----------| | 1,412 | 0.007 | ## 许可问题说明 尽管我们致力于打造许可信息完全准确的数据集，但许可洗白（license laundering）与元数据不准确的问题可能导致我们错误地为部分文档分配了错误的许可协议（关于此局限性的进一步讨论，请参阅[我们的论文](https://huggingface.co/papers/2506.05209)）。若您发现本数据集中存在许可信息错误的案例，请在本仓库[发起讨论](https://github.com/r-three/common-pile/discussions/new)。 ## 其他版本 本数据集为公有领域评论数据集的「原始版」。若您寻找用于训练[Comma v0.1](https://huggingface.co/common-pile/comma-v0.1)的过滤版数据集，可前往[此处](https://huggingface.co/datasets/common-pile/public_domain_review_filtered)获取。 ## 引用格式 若您使用本数据集，请引用如下文献： bibtex @article{kandpal2025common, title={{The Common Pile v0.1: An 8TB Dataset of Public Domain and Openly Licensed Text}}, author={Nikhil Kandpal and Brian Lester and Colin Raffel and Sebastian Majstorovic and Stella Biderman and Baber Abbasi and Luca Soldaini and Enrico Shippole and A. Feder Cooper and Aviya Skowron and Shayne Longpre and Lintang Sutawika and Alon Albalak and Zhenlin Xu and Guilherme Penedo and Loubna Ben and Elie Bakouch and John David and Honglu Fan and Dashiell Stander and Guangyu Song and Aaron Gokaslan and John Kirchenbauer and Tom Goldstein and Brian R and Bhavya Kailkhura and Tyler Murray}, journal={arXiv preprint}, year={2025} }

搜集汇总

背景与挑战

背景概述

Public Domain Review数据集收集了所有在CC BY-SA许可下发布的Public Domain Review在线期刊文章，专注于探索已进入公共领域的艺术与文学作品。该数据集包含1,412个文档，总大小为0.007 GB，采用Apache License 2.0许可。