论文标题
中心：段落级中文数据集用于企业之间的关系提取
CEntRE: A paragraph-level Chinese dataset for Relation Extraction among Enterprises
论文作者
论文摘要
企业关系提取旨在检测成对的企业实体，并从非结构化或半结构化文本数据中确定它们之间的业务关系，这对于几种现实世界中的应用程序（例如风险分析，评级研究和供应链安全）至关重要。但是，以前的工作主要集中于获取有关人员和公司业务等企业的属性信息，并且对企业关系提取的关注很少。为了鼓励研究进一步的进展，我们介绍了中心，该中心是一个新的数据集，该数据集由仔细的人类注释和智能数据处理的公开商业新闻数据构建。六个出色模型的中央实验广泛的实验证明了我们提出的数据集的挑战。
Enterprise relation extraction aims to detect pairs of enterprise entities and identify the business relations between them from unstructured or semi-structured text data, and it is crucial for several real-world applications such as risk analysis, rating research and supply chain security. However, previous work mainly focuses on getting attribute information about enterprises like personnel and corporate business, and pays little attention to enterprise relation extraction. To encourage further progress in the research, we introduce the CEntRE, a new dataset constructed from publicly available business news data with careful human annotation and intelligent data processing. Extensive experiments on CEntRE with six excellent models demonstrate the challenges of our proposed dataset.
