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GraphRAG in (Almost) Pure Cypher

Blog post from Neo4j

Post Details
Company
Date Published
Author
Christoffer Bergman
Word Count
1,503
Company Posts That Month
20
Language
English
Hacker News Points
-
Post removed?
No
Summary

GraphRAG is a method for using vector search to find relevant documents in a knowledge graph, with the goal of providing more accurate and reliable answers to questions. The author demonstrates this by building a graph of movies and TV series, and then uses GraphRAG to ask ChatGPT a question about Robb Stark's family, which it correctly answers based on the synopsis of a relevant document. However, when asked a question about a movie that was released after ChatGPT's training data, it hallucinates an answer instead of saying "I don't know". The author suggests using GraphRAG to improve the accuracy and reliability of AI-powered chatbots like ChatGPT by leveraging the power of knowledge graphs.

Trends Found in this Post
Trend Post Mentions Total Month Mentions Posts Companies MoM
Vector Search 19 1,644 222 91 +2%
RAG 7 1,642 187 75 +52%
LLM 1 4,157 383 131 +53%
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