yao8839836/kg-llm
Exploring large language models for knowledge graph completion. ICASSP 2025
This project helps machine learning researchers explore and implement methods for completing knowledge graphs using large language models. It takes existing knowledge graph data, along with entity and relation descriptions, and processes it through fine-tuned LLMs like LLaMA and ChatGLM. The output is predictions for missing links or entities within the knowledge graph. This is primarily for researchers and practitioners in natural language processing and knowledge representation.
161 stars. No commits in the last 6 months.
Use this if you are a researcher or advanced practitioner working with knowledge graphs and want to experiment with large language models to predict missing relationships or entities within them.
Not ideal if you are looking for an out-of-the-box solution for general knowledge graph construction or completion without deep expertise in fine-tuning large language models.
Stars
161
Forks
12
Language
Python
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Last pushed
Aug 23, 2025
Commits (30d)
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