graphrag and llm-graph-builder
These are **complements**: GraphRAG provides the RAG framework and query patterns while LLM Graph Builder supplies the upstream graph construction pipeline from unstructured data, making them useful in sequence within the same workflow.
About graphrag
microsoft/graphrag
A modular graph-based Retrieval-Augmented Generation (RAG) system
This system helps you make sense of large amounts of unstructured text data, like research papers or internal documents. It processes your text to identify key entities and relationships, outputting a structured knowledge graph that your AI can then use to answer complex questions or find insights more effectively. This is designed for researchers, analysts, or anyone who needs to extract precise information and reasoning from extensive narrative data using large language models.
About llm-graph-builder
neo4j-labs/llm-graph-builder
Neo4j graph construction from unstructured data using LLMs
This tool helps researchers, analysts, and knowledge managers transform disorganized information like PDFs, web pages, or video transcripts into a structured, interconnected knowledge graph. You feed it unstructured documents from various sources, and it outputs an organized Neo4j knowledge graph, making it easier to visualize connections and ask complex questions about your data.
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