In recent years, Question Answering (QA) systems have gained significant attention due to their ability to provide precise and context-aware information retrieval. However, the effectiveness of QA systems relies heavily on the quality and domain specificity of the datasets used for training and evaluation. In this study, we present Saigon Tourism, a curated dataset specifically designed to address the needs of QA systems in the tourism domain, focusing on Ho Chi Minh City (Saigon), Vietnam. The dataset encompasses a wide range of tourism-related topics, including landmarks, cuisine, accommodation, transportation, cultural events, and local insights, ensuring a comprehensive resource for both researchers and developers. We outline the dataset creation process, including data collection, annotation, and quality control, and evaluate its applicability in real-world QA scenarios. By leveraging Saigon Tourism, we aim to enhance the capabilities of domain-specific QA systems and contribute to the growing body of resources for AI-driven tourism applications.