Due to the increasing use of the Internet, the development of the information society, and public awareness about health, many patients are using the Internet to find health information. In addition, medical field information retrieval is exploding to retrieve specific medical knowledge about diseases due to the current corona pandemic and the prevalence of mobile handsets such as smartphones. Currently, much of the knowledge information in the medical field is provided in ontology, a method of expressing knowledge information. However, medical knowledge built in this ontology form requires the general user to know basic logic-based representations of ontology, such as the web ontology language OWL and semantic web technologies, for searching. Furthermore, the usage and understanding of the SPARQL protocol and RDF query language (SPARQL), a formalized query language in the form of ontology, is essential. To overcome the limitations of this ontology form of knowledge retrieval, this paper proposes the stroke medical ontology question and answering (QA) system that can analyze user medical knowledge in natural language form for medical knowledge curation services and automatically convert it to the structured query language, SPARQL. The proposed system analyzes questions and answers through query analysis, abstracts each syntax word through top-level medical ontology, and deduces the structured query template for abstracted questions and answers based on SWRL to complete the structured query template.