Benchmarks
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Subtasks
Datasets
Greatest papers with code
Recurrent Event Network: Autoregressive Structure Inference over Temporal Knowledge Graphs
• dmlc/dgl
• 
The task becomes more challenging on temporal knowledge graphs, where each fact is associated with a timestamp.
OpenKE: An Open Toolkit for Knowledge Embedding
We release an open toolkit for knowledge embedding (OpenKE), which provides a unified framework and various fundamental models to embed knowledge graphs into a continuous low-dimensional space.
INFORMATION RETRIEVAL KNOWLEDGE GRAPHS QUESTION ANSWERING REPRESENTATION LEARNING
Probability Calibration for Knowledge Graph Embedding Models
ICLR 2020
• Accenture/AmpliGraph
• 
We show popular embedding models are indeed uncalibrated.
CALIBRATION FOR LINK PREDICTION KNOWLEDGE GRAPH EMBEDDING KNOWLEDGE GRAPHS
Knowledge Graph Completion via Complex Tensor Factorization
In statistical relational learning, knowledge graph completion deals with automatically understanding the structure of large knowledge graphs---labeled directed graphs---and predicting missing relationships---labeled edges.
Ranked #2 on
Knowledge Graphs
on FB15k
KNOWLEDGE GRAPH COMPLETION LINK PREDICTION RELATIONAL REASONING
Holographic Embeddings of Knowledge Graphs
Learning embeddings of entities and relations is an efficient and versatile method to perform machine learning on relational data such as knowledge graphs.
Ranked #6 on
Link Prediction
on FB15k
Modeling Relational Data with Graph Convolutional Networks
• tkipf/gae
•
We demonstrate the effectiveness of R-GCNs as a stand-alone model for entity classification.
Ranked #1 on
Node Classification
on AIFB
GRAPH CLASSIFICATION INFORMATION RETRIEVAL KNOWLEDGE BASE COMPLETION KNOWLEDGE GRAPHS LINK PREDICTION NODE CLASSIFICATION
ERNIE: Enhanced Language Representation with Informative Entities
ACL 2019
• thunlp/ERNIE
•
Neural language representation models such as BERT pre-trained on large-scale corpora can well capture rich semantic patterns from plain text, and be fine-tuned to consistently improve the performance of various NLP tasks.
Ranked #1 on
Entity Linking
on FIGER
ENTITY LINKING ENTITY TYPING KNOWLEDGE GRAPHS LINGUISTIC ACCEPTABILITY NATURAL LANGUAGE INFERENCE PARAPHRASE IDENTIFICATION SENTIMENT ANALYSIS
OGB-LSC: A Large-Scale Challenge for Machine Learning on Graphs
We show that the expressive models significantly outperform simple scalable baselines, indicating an opportunity for dedicated efforts to further improve graph ML at scale.
Ranked #1 on
Node Classification
on MAG240M-LSC
GRAPH LEARNING GRAPH REGRESSION KNOWLEDGE GRAPHS LINK PREDICTION NODE CLASSIFICATION
Open Graph Benchmark: Datasets for Machine Learning on Graphs
NeurIPS 2020
• snap-stanford/ogb
•
We present the Open Graph Benchmark (OGB), a diverse set of challenging and realistic benchmark datasets to facilitate scalable, robust, and reproducible graph machine learning (ML) research.
Knowledge Graphs
• shaoxiongji/awesome-knowledge-graph
•
In this paper we provide a comprehensive introduction to knowledge graphs, which have recently garnered significant attention from both industry and academia in scenarios that require exploiting diverse, dynamic, large-scale collections of data.