Google, Microsoft, LinkedIn, and many more tech companies are using Graph RAG. Why? Let’s understand it by building one from scratch.
You may not realize it, but you’ve been interacting with Knowledge Graphs (KGs) more frequently than you might think. They’re the technology behind many modern search engines, Retrieval-Augmented Generation (RAG) systems for Large Language Models (LLMs), and various query tools. But what exactly are Knowledge Graphs, and why are they so integral to these technologies? Let’s delve into it.
A Knowledge Graph (KG) is a structured representation of information that captures real-world entities and the relationships between them. Imagine a network where each point represents an entity — such as a product, person, or concept — and the lines connecting them represent the relationships they share. This interconnected web allows for a rich semantic understanding of data, where the focus isn’t just on individual pieces of information but on how these pieces relate to one another.
Nodes
At the heart of a knowledge graph are nodes (entities). To illustrate this, let’s consider building a…
