amyguan/newswire-30-40-labor

该数据集包含新闻文章及其相关元数据，涵盖了多个主题标签（如反垄断、民权、犯罪等）、命名实体识别（NER）信息、地理位置信息、提及的人物信息等。数据集的结构包括文章、作者、日期、报纸元数据等特征。训练集包含24,006个样本，总大小为119,648,060.35745402字节。

This dataset contains news articles and their associated metadata, covering multiple topic labels (such as antitrust, civil rights, crime, etc.), named entity recognition (NER) information, geographic location information, mentioned person information, etc. The structure of the dataset includes features such as articles, bylines, dates, newspaper metadata, etc. The training set contains 24,006 samples with a total size of 119,648,060.35745402 bytes.