Virus multi-Semantic Annotation Dataset

<p><span>In-depth research into the characteristics of high-risk oncogenic viruses is of paramount scientific significance for the early prevention and control of related cancers and the development of effective vaccines. The mechanism of viral carcinogenesis involves numerous risk factors, including viral genomic variations, lifestyle, and environmental factors. Based on literature data on 8 oncogenic viruses, we have created a large-scale, semantically rich corpus of viral carcinogenic factors, including 551,715 abstracts and 5,821,308 entities using natural language processing technology combined with expert knowledge. The dataset includes annotation information for eight viruses: HPV, HIV, EBV, MCV, HCV, HTLV-1, HBV, and KSHV, covering 38 external factors and 5 internal factors.</span></p>