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CEntRE: A paragraph-level Chinese dataset for Relation Extraction among Enterprises

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arxiv 2210.10581 v1 pith:3HHSU4U2 submitted 2022-10-19 cs.CL cs.CR

CEntRE: A paragraph-level Chinese dataset for Relation Extraction among Enterprises

classification cs.CL cs.CR
keywords businesscentredatadatasetenterpriseextractionrelationenterprises
verification ladder T0 review T1 audit T2 compute T3 formal T4 reserved
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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.

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