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Demo|Building and Querying Knowledge Graph using Natural Language with NebulaGraph

Background Introduction

As a performance-leading native distributed graph database, NebulaGraph has now implemented the integration of large language models and graph query language application framework. Users can now achieve schema acquisition, Prompt for Cypher statement generation, invocation of various large language models (LLM), and result processing purely with natural language, without the need for any coding. This greatly reduces the learning and usage costs.

Demo Experience

Usage Instructions

Using information from "Guardians of the Galaxy Vol.3" on Wikipedia as an example, this demo demonstrates how NebulaGraph uses large language models (LLM) to help users extract knowledge triplets from different types of information sources purely with natural language, and store them in NebulaGraph database.

You can click on other tabs to experience the visualization of NebulaGraph, Cypher query, natural language query (Text2Cypher), and other features. For more information, please refer to "Graph + LLM Practical Guide | Building and Querying Knowledge Graph using Natural Language".

Without further ado, let's experience the fun of building and querying knowledge graphs using natural language with NebulaGraph!