JoelMba/MantraGSC_emea_CAS_annotations_combined_v2

该数据集名为MantraGSC_emea_CAS_annotations_combined_v2，是一个用于命名实体识别（NER）任务的数据集，专注于医疗或健康领域，特别是疾病或障碍的实体标注。数据集包含三个分割：训练集（56个例子）、验证集（12个例子）和测试集（7个例子）。每个例子包括id、tokens（文本序列）、ner_tags（序列标注，使用BIO格式，类别为B-Disorders、I-Disorders和O）和ner_tag_labels（对应的标签字符串）。数据总大小约为49.8KB，下载大小为18.3KB。该数据集可能用于训练和评估医疗文本中的实体识别模型，支持自然语言处理在医疗信息提取中的应用。

The dataset, named MantraGSC_emea_CAS_annotations_combined_v2, is designed for Named Entity Recognition (NER) tasks, focusing on the medical or health domain, specifically for annotating disease or disorder entities. It includes three splits: train (56 examples), validation (12 examples), and test (7 examples). Each example consists of id, tokens (text sequence), ner_tags (sequence annotations in BIO format with classes B-Disorders, I-Disorders, and O), and ner_tag_labels (corresponding label strings). The total dataset size is approximately 49.8KB, with a download size of 18.3KB. This dataset is likely used for training and evaluating entity recognition models in medical texts, supporting natural language processing applications in healthcare information extraction.