Objective To construct a knowledge graph for bone and soft tissue sarcoma and for nausea-vomiting symptom management, aiming to provide a systematic and visual tool for nursing education, health education, and symptom management in this field.Methods A top-down approach was adopted. Knowledge from various sources, including real-world clinical cases, relevant books, guidelines, expert consensus, and evidence summaries were integrated. Domain ontology and relationship definitions were performed to construct the schema layer. A combination of manual labeling and named entity recognition was employed, and Bert-BiLSTM-CRF was applied for knowledge modeling and extraction, to build the data layer. Then the knowledge graph was stored using Neo4j and presented visually via a Web interface. Results The knowledge graph comprises three main components:a disease case graph, a disease knowledge graph, and a symptom management graph, with 406 disease case entities, 278 disease knowledge entities, and 311 nausea-vomiting symptom management entities, which connected through 48 types of relationships. Conclusion This knowledge graph clearly and intuitively represents the knowledge structure of disease information and symptom management for bone and soft tissue sarcoma. It offers both visualization and convenient search functions, providing foundational support for the future development of question-answering system and clinical decision support system.