hhy-huang/GraphJudge
[EMNLP'25 main] This is the official repo for the paper, Can LLMs be Good Graph Judge for Knowledge Graph Construction?
This project helps knowledge engineers and researchers refine automatically generated knowledge graphs. It takes an initial set of text data and candidate knowledge graph triples (subject-predicate-object statements) and outputs a higher-quality, filtered knowledge graph with inaccurate information removed. It's designed for professionals building or evaluating knowledge bases who need to ensure the accuracy of machine-generated facts.
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Use this if you need to improve the precision of knowledge graphs automatically extracted from text, especially when dealing with noisy or uncertain data from large language models.
Not ideal if you are looking for a tool to generate knowledge graphs from scratch without a judging or filtering step, or if your primary focus is on other aspects of knowledge graph construction like entity linking or ontology alignment.
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Language
Python
License
MIT
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Last pushed
Sep 23, 2025
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