FR2KG

First, 1,200 financial research reports were collected. Experts in the financial field analyzed these reports, extracted the plain text from the main body, and saved it in the TXT format as the basic unstructured text corpus. Then, the experts and the knowledge graph team studied these corpora together, designed the schema of the knowledge graph from the perspective of financial business, and performed iterative optimization according to the characteristics of the evaluation, and finally, determined that it contained 10 entity types, 6 entity attributes, and 19 relationships between the entities. Subsequently, these corpora were annotated with the help of the annotation system of the Yuanhai Knowledge Graph Platform, which is a product of DataGrand Inc. The annotation system is specifically used for the annotation of the knowledge graph, and supports the annotation of entities, entity attributes, and relationships between entities. Before annotating, all annotators were trained by financial experts to align their understanding of the schema. All annotated data were reviewed by experts, and then, divided into seed KG and evaluation KG, as described in the previous section. Reference：Wang, W.G., et al.: Data set and evaluation of automated construction of financial knowledge graph. Data Intelligence 3(3), (2021). doi: 10.1162/dint_a_00108