uzair921/LLAMA_GUM_EMBEDDINGS_LLM_RAG_75_openai

该数据集是一个用于命名实体识别的任务的数据集，包含了 tokens 和 ner_tags 两个特征。tokens 是文本的词序列，ner_tags 是对应的实体标签序列，标签类型包括人名、地点、组织、事件、物体、植物、动物等，并且区分了实体的开始和延续。数据集分为训练集、验证集和测试集，共包含约829,714个字节的数据，具体划分为992个训练示例、615个验证示例和807个测试示例。

This dataset is for named entity recognition tasks, including two features: tokens and ner_tags. Tokens are the sequence of words in the text, and ner_tags are the corresponding entity label sequences, which include entity types such as person names, places, organizations, events, objects, plants, animals, etc., and distinguish between the beginning and continuation of entities. The dataset is divided into training, validation, and test sets, containing a total of about 829,714 bytes of data, specifically divided into 992 training examples, 615 validation examples, and 807 test examples.