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CoDEx: A Comprehensive Knowledge Graph Completion Benchmark

arXiv 2009.07810 ↗First posted 16 Sep 2020cs.CL cs.AI cs.IRcited by 102

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Abstract (arXiv)

We present CoDEx, a set of knowledge graph completion datasets extracted from Wikidata and Wikipedia that improve upon existing knowledge graph completion benchmarks in scope and level of difficulty. In terms of scope, CoDEx comprises three knowledge graphs varying in size and structure, multilingual descriptions of entities and relations, and tens of thousands of hard negative triples that are plausible but verified to be false. To characterize CoDEx, we contribute thorough empirical analyses and benchmarking experiments. First, we analyze each CoDEx dataset in terms of logical relation patterns. Next, we report baseline link prediction and triple classification results on CoDEx for five extensively tuned embedding models. Finally, we differentiate CoDEx from the popular FB15K-237 knowledge graph completion dataset by showing that CoDEx covers more diverse and interpretable content, and is a more difficult link prediction benchmark. Data, code, and pretrained models are available at https://bit.ly/2EPbrJs.

Key facts. Cited by 102 papers in the map (data through 7 Oct 2026). First posted on arXiv 16 Sep 2020.

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Citing papers per year: 2021: 4; 2022: 15; 2023: 20; 2024: 18; 2025: 25; 2026: 20.

102 papers.

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  1. 2022A Survey of Knowledge Graph Reasoning on Graph Types: Static, Dynamic, and Multimodalcited by 106
  2. 2023Towards Foundation Models for Knowledge Graph Reasoningcited by 83
  3. 2021NodePiece: Compositional and Parameter-Efficient Representations of Large Knowledge Graphscited by 71
  4. 2023Making Large Language Models Perform Better in Knowledge Graph Completioncited by 48
  5. 2024Mosaic of Modalities: A Comprehensive Benchmark for Multimodal Graph Learningcited by 28
  6. 2022An Open Challenge for Inductive Link Prediction on Knowledge Graphscited by 26
  7. 2024A Prompt-Based Knowledge Graph Foundation Model for Universal In-Context Reasoningcited by 25
  8. 2025TRIX: A More Expressive Model for Zero-shot Domain Transfer in Knowledge Graphscited by 23
  9. 2025How Expressive are Knowledge Graph Foundation Models?cited by 22
  10. 2023Evaluating Language Models for Knowledge Base Completioncited by 20
  11. 2023Toward Degree Bias in Embedding-Based Knowledge Graph Completioncited by 17
  12. 2021Node Co-occurrence based Graph Neural Networks for Knowledge Graph Link Predictioncited by 12
38 more
  1. 2022ReFactor GNNs: Revisiting Factorisation-based Models from a Message-Passing Perspectivecited by 12
  2. 2023Construction of Knowledge Graphs: State and Challengescited by 12
  3. 2023Sem@K: Is my knowledge graph embedding model semantic-aware?cited by 10
  4. 2021Are Missing Links Predictable? An Inferential Benchmark for Knowledge Graph Completioncited by 9
  5. 2022GreenKGC: A Lightweight Knowledge Graph Completion Methodcited by 9
  6. 2023Evaluating the Knowledge Base Completion Potential of GPTcited by 9
  7. 2022Swift and Sure: Hardness-aware Contrastive Learning for Low-dimensional Knowledge Graph Embeddingscited by 8
  8. 2023Entity-Agnostic Representation Learning for Parameter-Efficient Knowledge Graph Embeddingcited by 8
  9. 2025Flock: A Knowledge Graph Foundation Model via Learning on Random Walkscited by 8
  10. 2022Re-thinking Knowledge Graph Completion Evaluation from an Information Retrieval Perspectivecited by 7
  11. 2025SEMMA: A Semantic Aware Knowledge Graph Foundation Modelcited by 7
  12. 2025HYPER: A Foundation Model for Inductive Link Prediction with Knowledge Hypergraphscited by 7
  13. 2024Large Language Model Enhanced Knowledge Representation Learning: A Surveycited by 6
  14. 2024Towards Graph Foundation Models: Training on Knowledge Graphs Enables Transferability to General Graphscited by 6
  15. 2022CascadER: Cross-Modal Cascading for Knowledge Graph Link Predictioncited by 5
  16. 2024KGValidator: A Framework for Automatic Validation of Knowledge Graph Constructioncited by 5
  17. 2022PIE: a Parameter and Inference Efficient Solution for Large Scale Knowledge Graph Embedding Reasoningcited by 4
  18. 2022Relational representation learning with spike trainscited by 4
  19. 2022KGxBoard: Explainable and Interactive Leaderboard for Evaluation of Knowledge Graph Completion Modelscited by 4
  20. 2025MuCo-KGC: Multi-Context-Aware Knowledge Graph Completioncited by 4
  21. 2025Enhancing Large Language Model for Knowledge Graph Completion via Structure-Aware Alignment-Tuningcited by 4
  22. 2021Two-view Graph Neural Networks for Knowledge Graph Completioncited by 3
  23. 2023Random Entity Quantization for Parameter-Efficient Compositional Knowledge Graph Representationcited by 3
  24. 2023Distance-Based Propagation for Efficient Knowledge Graph Reasoningcited by 3
  25. 2023Prompting Disentangled Embeddings for Knowledge Graph Completion with Pre-trained Language Modelcited by 3
  26. 2023Do Similar Entities have Similar Embeddings?cited by 3
  27. 2024MQuinE: a cure for "Z-paradox" in knowledge graph embedding modelscited by 3
  28. 2024Fully Hyperbolic Rotation for Knowledge Graph Embeddingcited by 3
  29. 2022LEMON: LanguagE ModeL for Negative Sampling of Knowledge Graph Embeddingscited by 2
  30. 2022Explaining Link Predictions in Knowledge Graph Embedding Models with Influential Examplescited by 2
  31. 2023Revisiting Inferential Benchmarks for Knowledge Graph Completioncited by 2
  32. 2023Event Prediction using Case-Based Reasoning over Knowledge Graphscited by 2
  33. 2023Know2BIO: A Comprehensive Dual-View Benchmark for Evolving Biomedical Knowledge Graphscited by 2
  34. 2024PAC-Bayesian Generalization Bounds for Knowledge Graph Representation Learningcited by 2
  35. 2024Filter-then-Generate: Large Language Models with Structure-Text Adapter for Knowledge Graph Completioncited by 2
  36. 2024Have We Designed Generalizable Structural Knowledge Promptings? Systematic Evaluation and Rethinkingcited by 2
  37. 2025On Large-scale Evaluation of Embedding Models for Knowledge Graph Completioncited by 2
  38. 2025Decoupling and Damping: Structurally-Regularized Gradient Matching for Multimodal Graph Condensationcited by 2

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