Customizing property graph index in LlamaIndex

A guest post by Neo4J explores how to implement entity deduplication and custom retrieval methods to enhance the accuracy of GraphRAG using the property graph index within LlamaIndex. This integration represents an upgrade from previous knowledge graph frameworks by offering a modular approach that allows the use of various or custom graph constructors and retrievers. The post discusses constructing a knowledge graph using schema-guided extraction, performing entity deduplication via text embedding and word similarity techniques, and designing a custom graph retriever. It also outlines the environment setup using Neo4j as the graph store and employs a sample news article dataset to demonstrate the process. The flexibility of this system allows users to tailor components to specific requirements, exemplified by the creation of a custom retriever that identifies entities in input queries for more precise data retrieval. The blog post concludes by showcasing the application of these techniques in a question-answering flow, with all related code made available on GitHub for further exploration.

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