RManLuo/ChatRule

Mining Logical Rules with Large Language Models for Knowledge Graph Reasoning with 1 dollar.

39
/ 100
Emerging

This tool helps researchers and data scientists discover underlying logical connections within large knowledge graphs. By inputting an existing knowledge graph, it uses large language models to generate and refine logical rules that describe how different entities and relationships are connected. The output is a set of interpretable rules that can be used to perform reasoning and predict missing information within your knowledge graph without needing to train complex AI models.

No commits in the last 6 months.

Use this if you need to understand the hidden logical relationships in your knowledge graphs and want to use these insights for automated reasoning or to fill in missing data points.

Not ideal if you are looking for a tool to build or visualize knowledge graphs from unstructured text, or if you need to perform numerical predictions rather than logical deductions.

knowledge-graph-reasoning data-science-research semantic-networks logical-inference AI-explanation
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 9 / 25
Maturity 16 / 25
Community 14 / 25

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Stars

74

Forks

11

Language

Python

License

MIT

Last pushed

Jan 22, 2024

Commits (30d)

0

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