Hyper-Extract
🔧 Toolyifanfeng97
One-command CLI turning unstructured text into knowledge graphs, hypergraphs, and spatio-temporal data using LLMs.
Hyper-Extract is a lightweight, command-line interface tool designed to bridge the gap between unstructured text and structured knowledge representations. Built in Python, it leverages LLMs to automatically extract entities, relationships, and complex relational structures from raw text, outputting them as graphs, hypergraphs, or spatio-temporal formats. The tool supports multiple extraction modes, allowing users to choose the most appropriate representation for their use case — from simple entity-relation triples to higher-order hypergraphs that capture multi-entity interactions, and spatio-temporal data for time-aware and location-aware knowledge. With 1,351 GitHub stars and 151 forks, Hyper-Extract integrates naturally into AI agent workflows, RAG pipelines, and knowledge graph construction pipelines. Its single-command design makes it accessible to both researchers and engineers who need quick, reliable information extraction without building custom NLP pipelines. The tool addresses key challenges in knowledge engineering by automating what traditionally required manual annotation or complex multi-stage NLP pipelines.
💡Highlights
- ├─Graph, hypergraph & spatio-temporal modes
- ├─One-command CLI for LLM extraction
- └─Plug-and-play for RAG & agents
🎯For
- ├─AI/ML engineers
- ├─Knowledge graph researchers
- └─AI agent developers