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knowledge graph

Applied AI interview questions tagged knowledge graph, across every topic.

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Concepts behind "knowledge graph"

The curriculum that explains the ideas these questions test.

Core
🤖 Retrieval & AgentsSign in
GraphRAG and Knowledge-Graph RetrievalGraphRAG builds an entity-and-relationship graph over a corpus, then retrieves by traversing that graph instead of (or alongside) flat vector similarity. It answers the questions flat RAG fails on: multi-hop connections that span documents and global questions that need the whole corpus summarized, not the top-k chunks. The catch is build and maintenance cost: extracting entities and relations with an LLM is expensive and the graph drifts as the corpus changes. Applied-AI interviews probe it to see if you know when the extra machinery actually pays off.
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