SecureFinAI-Lab/Regulations_NER

这是一个用于评估大型语言模型在金融监管文本中进行命名实体识别能力的数据集，专注于欧洲场外衍生品市场，受EMIR监管。数据集中的实体包括组织、立法、日期、货币价值和统计数据。数据集由ESMA提供，共有49个与EMIR相关的条目，使用F1分数作为评估指标。

This dataset is designed to evaluate the ability of large language models in named entity recognition (NER) within financial regulatory texts, focusing on the European OTC derivative market regulated under EMIR. The entities in the dataset include organizations, legislation, dates, monetary values, and statistics. Provided by ESMA, the dataset contains 49 items related to EMIR, with the F1 score as the evaluation metric.