Graph RAG Interview Questions

Q1 What is Graph RAG? Generate → Q2 How does Graph RAG improve retrieval compared to vector search? Generate → Q3 What is the purpose of a graph generator in Graph RAG? Generate → Q4 Explain how a graph database is used in Graph RAG. Generate → Q5 What is Graph RAG and how does it differ from traditional RAG? Generate → Q6 What is a knowledge graph in the context of Graph RAG? Generate → Q7 How does Graph RAG use graph databases for retrieval? Generate → Q8 What are nodes and edges in a knowledge graph? Generate → Q9 How are relationships represented in Graph RAG systems? Generate → Q10 What are the advantages of using Graph RAG over vector-based RAG? Generate → Q11 How does entity extraction help build a knowledge graph for RAG? Generate → Q12 What role does graph traversal play in Graph RAG? Generate → Q13 What are common graph databases used for Graph RAG? Generate → Q14 How does Graph RAG improve contextual understanding? Generate → Q15 What is the role of semantic relationships in Graph RAG retrieval? Generate → Q16 How does Graph RAG handle complex multi-hop queries? Generate → Q17 What is multi-hop reasoning in Graph RAG? Generate → Q18 How does Graph RAG improve answer accuracy compared to naive RAG? Generate → Q19 What challenges exist when implementing Graph RAG? Generate → Q20 How are documents converted into graph structures in Graph RAG? Generate →