As the global economy has expanded, animal diseases have become significant obstacles to the sustainable development of animal husbandry. Among these diseases, bovine rotavirus coronavirus (BCV or BCoV) exhibits clinical symptoms such as diarrhea, dehydration, and gastroenteritis. The prevention and control of BCV virus remain the primary concern in managing bovine viral diarrheal diseases. We using crawler technology to search for key words of  "bovine coronavirus" and "BCV" in the PubMed database, 1410 articles were obtained, and after screening, 927 related articles were obtained. A knowledge graph construction pipeline method called BcvKG has been proposed to convert unstructured data into structured data. We obtained 1422 entities and 584 pairs of valid entity triplets, and visualized them using the Neo4j graph database. Finally, presented in the form of a knowledge graph. Compared with previous methodological methods, this article has completed the information extraction of literature related to bovine viral diarrhea disease for the first time, aiming to construct a knowledge graph.