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.

翻译：企业关系提取的目的是从无结构或半结构文本数据中发现企业实体的对口,查明它们之间的商业关系,这对于风险分析、评级研究和供应链安全等几个现实世界应用至关重要,然而,以往的工作主要侧重于获取关于人事和公司业务等企业的属性信息,很少注意企业关系提取。为了鼓励进一步推进研究,我们引入了CEntRE,这是根据公开商业新闻数据构建的一套新数据集,有谨慎的人文说明和智能数据处理。CEntRE的广泛实验有6个优秀模型,展示了我们拟议数据集的挑战。