thunlp/OpenKE

Health v2 · maintenance only

Flags: no_releases no_license

Adoption not part of the score

4047 stars · 986 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

OpenKE is an open-source PyTorch-based toolkit for knowledge graph embedding (knowledge representation learning), with C++ accelerated data preprocessing and negative sampling. It implements classic models such as TransE, TransH, TransR, TransD, DistMult, ComplEx, RotatE, RESCAL, and SimplE, plus TensorFlow and lightweight C++ inference variants.

Use cases

• train knowledge graph embedding models
• run link prediction on knowledge graphs
• compute entity and relation embeddings for a knowledge base
• benchmark TransE, TransR, RotatE and other KRL models
• use knowledge embeddings for downstream NLP tasks

When to choose

• you need a well-established PyTorch framework for knowledge graph embedding research
• you want implementations of many classic KRL models in one toolkit
• you need GPU-accelerated training on large-scale knowledge graphs

When to avoid

• you need actively maintained code with recent bug fixes or a permissive license
• you want modern state-of-the-art embedding models beyond the classic TransX family
• you need a production system rather than a research toolkit

Facets

library · maturity maintenance

machine-learning deep-learning nlp machine-learning python cross-platform knowledge-graph knowledge-embedding pytorch link-prediction knowledge-representation-learning transe rotate research natural-language-processing algorithms gpu linux

Member repositories

For agents

markdown · JSON · MCP: product_card(name="thunlp/OpenKE")