ele-sage/person-company-names-classification

这是一个大规模、经过精心策划的数据集，包含超过700万个示例，专门设计用于训练二分类文本分类模型。主要任务是在人名和公司/组织名之间进行区分。数据集构建目的是为了训练一个能够处理各种名称格式的健壮分类器。数据集均衡，包含大量的人和公司名，适合对语言模型进行微调。

This is a large-scale, curated dataset containing over 7 million examples, designed specifically for training a binary text classification model. The primary task is to distinguish between a persons full name and a company/organization name. The dataset was built to train a robust classifier capable of handling various name formats. It is balanced, containing a large number of both person and company names, making it ideal for fine-tuning language models.