sarahooker/adaption-hacker-news-article-prompts

该数据集包含从Hacker News文章标题派生的文本生成提示，指示模型根据提供的或自生成的头条新闻撰写完整文章。样本包括来自Hacker News社区的特定技术和商业主题，以及模型必须从头开始发明标题的实例。它旨在训练或评估系统在长文本生成和标题扩展任务上的表现。数据集包含51个数据点，质量评级为B，相对质量提升58.0%。领域主要集中在写作编辑沟通（64%）、企业商业（21%）和市场营销（7%）。语言全部为英语，语气包括创意（29%）、信息性（21%）和幽默（14%）。

This dataset contains text generation prompts derived from Hacker News article titles, instructing models to write full articles based on provided or self-generated headlines. The samples include specific tech and business topics from the Hacker News community, as well as instances where the model must invent a title from scratch. It is designed for training or evaluating systems on long-form content generation and headline expansion tasks. There are 51 data points in this dataset, with a quality grade of B and a relative quality improvement of 58.0%. The domain is mainly Writing-editing-communication (64%), Corporate-business (21%), and Marketing (7%). The language is 100% English, and the tone includes Creative (29%), Informative (21%), and Humorous (14%).