intfloat/SimKGC
ACL 2022, SimKGC: Simple Contrastive Knowledge Graph Completion with Pre-trained Language Models
This project helps researchers and developers working with knowledge graphs to efficiently complete missing information. It takes existing knowledge graph data, often in text format, and uses advanced language models to predict new, accurate relationships between entities. The primary users are machine learning engineers and NLP researchers focused on knowledge representation and reasoning.
213 stars. No commits in the last 6 months.
Use this if you need to improve the accuracy and efficiency of filling in missing links within large knowledge graphs using state-of-the-art text-based methods.
Not ideal if you lack access to significant GPU resources (multiple high-memory GPUs) or if you are not comfortable with advanced machine learning model training and evaluation.
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Python
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Last pushed
Dec 24, 2022
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