Researchers compared Knowledge Graph-based augmentation and Retrieval Augmented Generation (RAG) for culturally-related question answering. Graph-RAG, which uses a knowledge graph built from Wikipedia articles, showed competitive results to standard RAG and improved the base LLM's accuracy by 72-78%. This has implications for the development of more inclusive and explainable AI models.