JoelMba/PARHAF_CASM2_guidelines

PARHAF_CASM2_guidelines数据集是一个用于命名实体识别（NER）任务的文本数据集，专注于疾病实体识别。数据集包含文本序列（tokens）和对应的NER标签（ner_tags），标签采用BIO标注方案，包括B-Disorders（疾病开始）、I-Disorders（疾病内部）和O（其他）。数据集分为训练集（3072个示例）和验证集（1181个示例），每个示例包含id、tokens、ner_tags和ner_tag_labels字段。数据集总大小约为53.6MB，适用于自然语言处理中的信息抽取和实体识别研究。

The PARHAF_CASM2_guidelines dataset is a text dataset designed for Named Entity Recognition (NER) tasks, specifically focusing on disorder entity recognition. It includes text sequences (tokens) and corresponding NER tags (ner_tags) using the BIO annotation scheme, with labels such as B-Disorders (beginning of disorder), I-Disorders (inside disorder), and O (other). The dataset is split into a training set (3,072 examples) and a validation set (1,181 examples), each containing fields for id, tokens, ner_tags, and ner_tag_labels. With a total size of approximately 53.6 MB, it is suitable for research in natural language processing, particularly in information extraction and entity recognition.