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Knowledge Graph Embeddings

3260 papers • 126 benchmarks • 313 datasets

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Benchmarks

These leaderboards are used to track progress in knowledge-graph-embeddings-1

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Dataset

Best Model

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Libraries

i

Use these libraries to find knowledge-graph-embeddings-1 models and implementations

pykeen/pykeen

2 papers 1,503

Datasets

MutualFriends

OLPBENCH

KGRC-RDF-star

GEval for KGRC-RDF-star

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Most implemented papers

Learning Hierarchy-Aware Knowledge Graph Embeddings for Link Prediction

Yongdong Zhang, Zhanqiu Zhang, Jie Wang, Jianyu Cai•Wed Nov 20 2019

A novel knowledge graph embedding model, Hierarchy-Aware Knowledge Graph Embedding (HAKE), which maps entities into the polar coordinate system and significantly outperforms existing state-of-the-art methods on benchmark datasets for the link prediction task.

452

Content

zjunlp/promptkg

2 papers 628

thu-keg/eakit

2 papers 183

dice-group/dice-embeddings

2 papers 35

nicolas-hbt/versatile-embeddings

2 papers 15

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Convolutional 2D Knowledge Graph Embeddings

Pontus Stenetorp, Sebastian Riedel, Pasquale Minervini, Tim Dettmers•Tue Jul 04 2017

ConvE, a multi-layer convolutional network model for link prediction, is introduced, and it is found that ConvE achieves state-of-the-art Mean Reciprocal Rank across all datasets.

2936 0

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KBGAN: Adversarial Learning for Knowledge Graph Embeddings

William Yang Wang, Liwei Cai•Fri Nov 10 2017

Inspired by generative adversarial networks (GANs), this framework uses one knowledge graph embedding model as a negative sample generator to assist the training of the desired model, which acts as the discriminator in GANs.

301 0

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Seq2RDF: An End-to-end Application for Deriving Triples from Natural Language Text

Heng Ji, Yue Liu, Tongtao Zhang, Zhicheng Liang, Deborah L. McGuinness•Tue Jul 03 2018

This work presents an end-to-end approach that takes unstructured textual input and generates structured output compliant with a given vocabulary and proposes an encoder-decoder framework with an attention mechanism that leverages knowledge graph embeddings.

26 0

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Multi-Hop Knowledge Graph Reasoning with Reward Shaping

R. Socher, Caiming Xiong, Xi Victoria Lin•Thu Aug 30 2018

This work reduces the impact of false negative supervision by adopting a pretrained one-hop embedding model to estimate the reward of unobserved facts and counter the sensitivity to spurious paths of on-policy RL by forcing the agent to explore a diverse set of paths using randomly generated edge masks.

375 0

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Low-Dimensional Hyperbolic Knowledge Graph Embeddings

Ines Chami, Christopher Ré, Da-Cheng Juan, Sujith Ravi, A. Wolf, Frederic Sala•Thu Apr 30 2020

This work introduces a class of hyperbolic KG embedding models that simultaneously capture hierarchical and logical patterns in KGs and observes that different geometric transformations capture different types of relations while attention- based transformations generalize to multiple relations.

447 0

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Prediction of Adverse Biological Effects of Chemicals Using Knowledge Graph Embeddings

Jiaoyan Chen, Ernesto Jiménez-Ruiz, E. B. Myklebust, Raoul Wolf, K. Tollefsen•Tue Dec 07 2021

It is shown that using knowledge graph embeddings can increase the accuracy of effect prediction with neural networks and implement a fine-tuning architecture which adapts the knowledge graphembeddings to the effect prediction task and leads to a better performance.

11 0

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Learning Entity and Relation Embeddings for Knowledge Graph Completion

Zhiyuan Liu, Yankai Lin, Maosong Sun, Xuan Zhu, Yang Liu•Sat Jan 24 2015

TransR is proposed to build entity and relation embeddings in separate entity space and relation spaces by first projecting entities from entity space to corresponding relation space and then building translations between projected entities.

3847 0

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Multilingual Knowledge Graph Embeddings for Cross-lingual Knowledge Alignment

Yingtao Tian, Muhao Chen, C. Zaniolo, Mohan Yang•Fri Nov 11 2016

MTransE, a translation-based model for multilingual knowledge graph embeddings, is proposed to provide a simple and automated solution to achieve cross-lingual knowledge alignment and explore how MTransE preserves the key properties of its monolingual counterpart.

593 0

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