Creating graphs from text is incredibly exciting, but definitely challenging. Essentially, it’s about converting unstructured text into structured data. While this approach has been around for some…

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This post explores building knowledge graphs using the LLM Graph Transformer from LangChain. It covers techniques for extracting structured data from unstructured text to create knowledge graphs, highlighting the advantages and challenges of both tool-based and prompt-based modes. The guide includes steps for setting up a Neo4j environment, defining graph schemas, and ensuring consistency in extraction. Additionally, it addresses how to import graph documents into databases like Neo4j for further analysis and application.

Building Knowledge Graphs with LLM Graph Transformer

<p>I have done quite a bit of knowledge graph dev with LLMs and I went into this article expecting to already know the content, but I was surprised to find I learned something in the process :P</p>
<p>Good stuff. Recommend reading.</p>
