This project advances artificial intelligence (AI) by developing more reliable and trustworthy question-answering systems that combine large language models with structured knowledge graphs. Current AI systems, while powerful in generating human-like responses, often produce answers that are plausible but factually incorrect, which can have severe consequences in critical domains like healthcare and legal services. By integrating the strengths of large language models with the structured, verifiable information from knowledge graphs, this research creates AI systems that people can trust for high-stakes decisions. The project develops novel computational methods that ensure AI outputs are grounded in verified knowledge, reducing errors and improving reliability. The research outcomes will benefit society by enabling more dependable AI assistants for healthcare diagnosis support, legal consultation, and other domains where accuracy is paramount. The project also contributes to computer science education through new courses on knowledge graphs and advanced language models at the University of California, Merced, helping prepare the next generation of AI researchers and practitioners. Open-source software tools and datasets developed through this research will be made freely available to the broader research community, accelerating progress in trustworthy AI development. The project develops innovative approaches for combining large language models with knowledge graphs throu