How to Build Knowledge Graph Generation Pipelines From Text With kg-gen, NetworkX Analytics, and Interactive Visualizations

A tutorial shows how to turn plain text and long passages into knowledge graphs with kg-gen.

It covers setup, LLM configuration, entity and relation extraction, chunking, clustering, and graph merging.

The workflow also uses NetworkX, PyVis, and Matplotlib to visualize, inspect, and analyze the resulting graph.

The result is a practical pipeline for turning unstructured text and multi-document sources into reusable graph data.