Skip to main content

Graph-based RAG (1/2) KG Creation

Steps

  1. Overview
  2. Pre-requisites
  3. Illustration of the Process Through an Example
  4. Expand Your Knowledge

1 Overview​

Description​

Large language models are good at understanding and generating text, but they need reliable sources of information to provide correct answers to real business questions. A Knowledge Graph (KG) is a smart way to organize facts and show how everything is connected. It combines data from tables, documents, and even expert knowledge. Using a knowledge graph can help AI to focus on real facts, so it makes fewer mistakes and gives you answers you can trust. Another important point is that it reduces the likelihood of LLMs hallucinating, as the context provided helps to clearly define the domain of knowledge.

Expected Outcome​

By creating a knowledge graph using best practices, you’ll get a clear and organized view of your data that shows how key concepts are connected. This helps the RAG system find more relevant information and give better answers.

The results include more accurate and trustworthy responses, fewer mistakes, and a system that’s easier to update and explain.