Vietnam boasts a thriving tourism sector that significantly contributes to its economy and digitalization has become crucial for enhancing the tourist experience. The application of Semantic Web technologies and ontologies has emerged as a promising approach for managing and retrieving tourism-related information. This paper presents the development of an ontology-based knowledge base focusing on Vietnamese cultural and historical tourism. Furthermore, we propose a methodology for constructing a chatbot capable of efficient information retrieval through natural language question answering from this knowledge base. The proposed method leverages the creation of an automatically generated training dataset for intent classification, utilizing information within the knowledge base to analyze questions and translate them into semantic queries. Experimental results demonstrate that the chatbot, built using our proposed approach, achieves a high accuracy of nearly 88%.