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Engines that use knowledge graphs to improve the accuracy of language model responses.
Distinguishing note: Defines the core engine capability for graph-based retrieval.
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GraphRAG is a data processing pipeline and retrieval engine designed to transform unstructured text into interconnected knowledge graphs. By utilizing language models to extract entities and relationships, it builds structured representations of information that enable context-aware retrieval for downstream applications. The system distinguishes itself through hierarchical graph clustering and large-scale data synthesis, which organize massive document corpora into multi-level structures. This approach allows for both vector-based semantic searches and graph-based traversals, providing a comp
Transforms unstructured text into interconnected knowledge graphs to improve the accuracy and context of language model responses.