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Awesome Knowledge Graph Embedding Model Software Awesome

This list contains awesome code for knowledge graph embedding models (KGEMs). It doesn't contain single model research repositories nor more general graph machine learning packages like PyTorch-Geometric.

Contents

  1. PyKEEN
  2. AmpliGraph
  3. Pykg2vec
  4. StellarGraph
  5. PyTorch-BigGraph
  6. Deep Graph Library
  7. Paddle Graph Learning
  8. CogKGE
  9. Marius
  10. GraphVite
  11. LibKGE
  12. OpenKE
  13. μKG

PyKEEN

GitHub Docs Docs

PyKEEN is a PyTorch-based KGEM library for training and evaluation of knowledge graph embedding models. It is built with a modular architecture so the model, loss function, training loop, and other components can be used interchangably.

PyKEEN 1.0: A Python Library for Training and Evaluating Knowledge Graph Embeddings
Mehdi Ali, Max Berrendorf, Charles Tapley Hoyt, Laurent Vermue, Sahand Sharifzadeh, Volker Tresp, and Jens Lehmann
JMLR, 2021

Install with:

$ pip install pykeen

AmpliGraph

GitHub Docs

AmpliGraph is a suite of neural machine learning models for relational Learning, a branch of machine learning that deals with supervised learning on knowledge graphs.

Install with:

$ pip install ampligraph

Pykg2vec

GitHub Docs

Pykg2vec is a library for learning the representation of entities and relations in Knowledge Graphs built on top of PyTorch 1.5 (TF2 version is available in tf-master branch as well). It attempts to bring state-of-the-art knowledge graph embedding algorithms and the necessary building blocks in the pipeline of knowledge graph embedding task into a single library.

Pykg2vec: A Python Library for Knowledge Graph Embedding
Shih-Yuan Yu, Sujit Rokka Chhetri, Arquimedes Canedo, Palash Goyal, and Mohammad Abdullah Al Faruque
JMLR, 2021

Install with:

$ pip install pykg2vec

StellarGraph

GitHub Docs

The StellarGraph library offers state-of-the-art algorithms for graph machine learning, making it easy to discover patterns and answer questions about graph-structured data.

Install with:

$ pip install stellargraph

PyTorch-BigGraph

GitHub Docs

PyTorch-BigGraph (PBG) is a distributed system for learning graph embeddings for large graphs, particularly big web interaction graphs with up to billions of entities and trillions of edges.

PyTorch-BigGraph: A Large-scale Graph Embedding Framework
Adam Lerer, Ledell Wu, Jiajun Shen, Timothee Lacroix, Luca Wehrstedt, Abhijit Bose, and Alex Peysakhovich
Proceedings of the 2nd SysML Conference, 2019

Install with:

$ pip install torchbiggraph

Deep Graph Library

GitHub Docs Docs

DGL is an easy-to-use, high performance and scalable Python package for deep learning on graphs. DGL is framework agnostic, meaning if a deep graph model is a component of an end-to-end application, the rest of the logics can be implemented in any major frameworks, such as PyTorch, Apache MXNet or TensorFlow.

Deep Graph Library: A Graph-Centric, Highly-Performant Package for Graph Neural Networks
Minjie Wang, Da Zheng, Zihao Ye, Quan Gan, Mufei Li, Xiang Song, Jinjing Zhou, Chao Ma, Lingfan Yu, Yu Gai, Tianjun Xiao, Tong He, George Karypis, Jinyang Li, and Zheng Zhang
arXiv, 2020

Install with:

$ pip install dgl

Paddle Graph Learning

GitHub Docs

Paddle Graph Learning (PGL) is an efficient and flexible graph learning framework based on PaddlePaddle.

Install with:

$ pip install pgl

CogKGE

GitHub Docs

A Knowledge Graph Embedding Toolkit and Benckmark for Representing Multi-source and Heterogeneous Knowledge

CogKGE: A Knowledge Graph Embedding Toolkit and Benchmark for Representing Multi-source and Heterogeneous Knowledge
Zhuoran Jin, Tianyi Men, Hongbang Yuan, Zhitao He, Dianbo Sui, Chenhao Wang, Zhipeng Xue, Yubo Chen, Jun Zhao
ACL, 2022

Install with:

$ pip install cogkge

Marius

GitHub Docs

Marius is a system for large-scale graph learning that supports large-scale link prediction training, and preprocessing and training of datasets.

Marius: Learning Massive Graph Embeddings on a Single Machine
Jason Mohoney, Roger Waleffe, Henry Xu, Theodoros Rekatsinas, and Shivaram Venkataraman
OSDI, 2021

Marius can't currently be installed directly from PyPI via pip. See its installation docs instead.

GraphVite

GitHub Docs

GraphVite is a general and high-performance graph embedding system for various applications, designed for CPU-GPU hybrid architecture.

GraphVite: A High-Performance CPU-GPU Hybrid System for Node Embedding
Zhaocheng Zhu, Shizhen Xu, Meng Qu, and Jian Tang
arXiv, 2019

GraphVite can't currently be installed directly from PyPI via pip. See its installation docs instead.

LibKGE

GitHub

LibKGE is a PyTorch-based library for efficient training, evaluation, and hyperparameter optimization of knowledge graph embeddings.

LibKGE - A knowledge graph embedding library for reproducible research
Samuel Broscheit, Daniel Ruffinelli, Adrian Kochsiek, Patrick Betz, and Rainer Gemulla
EMNLP, 2020

LibKGE can't currently be installed directly from PyPI via pip. See its installation docs instead.

OpenKE

GitHub Docs

OpenKE is an open-source framework for knowledge embedding organized by THUNLP based on the TensorFlow toolkit.

OpenKE: An Open Toolkit for Knowledge Embedding
Xu Han, Shulin Cao, Xin Lv, Yankai Lin, Zhiyuan Liu, Maosong Sun, and Juanzi Li
EMNLP, 2018

OpenKE can't currently be installed directly from PyPI via pip. See its installation docs instead.

μKG

GitHub

Warning This manuscript is not yet publicly available
μKG: A Library for Multi-source Knowledge Graph Embeddings and Applications
Xindi Luo, Zequn Sun, Wei Hu
ISWC, 2022

μKG can't currently be installed directly from PyPI via pip. See its installation docs instead.

Footnotes

The full list can be downloaded in YAML here.