mlsanityData to 7 Oct 2026

Embedding Entities and Relations for Learning and Inference in Knowledge Bases

arXiv 1412.6575 ↗First posted 20 Dec 2014cs.CLcited by 929

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Cited by 42 in LLM reasoning, but placed by its own abstract, which didn’t fit.

Abstract (arXiv)

We consider learning representations of entities and relations in KBs using the neural-embedding approach. We show that most existing models, including NTN (Socher et al., 2013) and TransE (Bordes et al., 2013b), can be generalized under a unified learning framework, where entities are low-dimensional vectors learned from a neural network and relations are bilinear and/or linear mapping functions. Under this framework, we compare a variety of embedding models on the link prediction task. We show that a simple bilinear formulation achieves new state-of-the-art results for the task (achieving a top-10 accuracy of 73.2% vs. 54.7% by TransE on Freebase). Furthermore, we introduce a novel approach that utilizes the learned relation embeddings to mine logical rules such as "BornInCity(a,b) and CityInCountry(b,c) => Nationality(a,c)". We find that embeddings learned from the bilinear objective are particularly good at capturing relational semantics and that the composition of relations is characterized by matrix multiplication. More interestingly, we demonstrate that our embedding-based rule extraction approach successfully outperforms a state-of-the-art confidence-based rule mining approach in mining Horn rules that involve compositional reasoning.

Key facts. Cited by 929 papers in the map (data through 7 Oct 2026). First posted on arXiv 20 Dec 2014.

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Citing papers per year: 2021: 179; 2022: 200; 2023: 195; 2024: 159; 2025: 115; 2026: 81.

929 papers.

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  1. 2023Unifying Large Language Models and Knowledge Graphs: A Roadmapcited by 663
  2. 2021Neural Bellman-Ford Networks: A General Graph Neural Network Framework for Link Predictioncited by 273
  3. 2022LinkBERT: Pretraining Language Models with Document Linkscited by 209
  4. 2021Are we really making much progress? Revisiting, benchmarking, and refining heterogeneous graph neural networkscited by 176
  5. 2022Deep Bidirectional Language-Knowledge Graph Pretrainingcited by 156
  6. 2023Large-scale Multi-Modal Pre-trained Models: A Comprehensive Surveycited by 153
  7. 2021Graph Learning: A Surveycited by 140
  8. 2021Hyperbolic Deep Neural Networks: A Surveycited by 138
  9. 2021Fully Hyperbolic Neural Networkscited by 107
  10. 2021Temporal Knowledge Graph Reasoning Based on Evolutional Representation Learningcited by 106
  11. 2022A Survey of Knowledge Graph Reasoning on Graph Types: Static, Dynamic, and Multimodalcited by 106
  12. 2022SimKGC: Simple Contrastive Knowledge Graph Completion with Pre-trained Language Modelscited by 90
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  1. 2023Towards Foundation Models for Knowledge Graph Reasoningcited by 83
  2. 2022Graph Neural Networks for Link Prediction with Subgraph Sketchingcited by 81
  3. 2021Graph Representation Learning in Biomedicinecited by 79
  4. 2022Sequence-to-Sequence Knowledge Graph Completion and Question Answeringcited by 75
  5. 2021From Statistical Relational to Neurosymbolic Artificial Intelligence: a Surveycited by 72
  6. 2023Graph Neural Prompting with Large Language Modelscited by 64
  7. 2021Temporal Knowledge Graph Forecasting with Neural ODEcited by 61
  8. 2022Neural-Symbolic Models for Logical Queries on Knowledge Graphscited by 60
  9. 2021TLogic: Temporal Logical Rules for Explainable Link Forecasting on Temporal Knowledge Graphscited by 59
  10. 2023InGram: Inductive Knowledge Graph Embedding via Relation Graphscited by 50
  11. 2022A*Net: A Scalable Path-based Reasoning Approach for Knowledge Graphscited by 49
  12. 2023Making Large Language Models Perform Better in Knowledge Graph Completioncited by 48
  13. 2022RHO (ρ): Reducing Hallucination in Open-domain Dialogues with Knowledge Groundingcited by 47
  14. 2021OntoZSL: Ontology-enhanced Zero-shot Learningcited by 45
  15. 2022From Discrimination to Generation: Knowledge Graph Completion with Generative Transformercited by 45
  16. 2022TorchDrug: A Powerful and Flexible Machine Learning Platform for Drug Discoverycited by 45
  17. 2022Hybrid Transformer with Multi-level Fusion for Multimodal Knowledge Graph Completioncited by 44
  18. 2022Knowledge Graph Contrastive Learning Based on Relation-Symmetrical Structurecited by 43
  19. 2023Exploring Large Language Models for Knowledge Graph Completioncited by 43
  20. 2022Temporal Knowledge Graph Reasoning with Historical Contrastive Learningcited by 42
  21. 2022Knowledge Graph Embedding: A Survey from the Perspective of Representation Spacescited by 41
  22. 2022T2G-Former: Organizing Tabular Features into Relation Graphs Promotes Heterogeneous Feature Interactioncited by 41
  23. 2025GFM-RAG: Graph Foundation Model for Retrieval Augmented Generationcited by 40
  24. 2021Search from History and Reason for Future: Two-stage Reasoning on Temporal Knowledge Graphscited by 39
  25. 2021A Survey on Neural-symbolic Learning Systemscited by 39
  26. 2023Heterogeneous Federated Knowledge Graph Embedding Learning and Unlearningcited by 39
  27. 2021Modeling Heterogeneous Hierarchies with Relation-specific Hyperbolic Conescited by 38
  28. 2021Universal Representation Learning of Knowledge Bases by Jointly Embedding Instances and Ontological Conceptscited by 37
  29. 2021Relation Prediction as an Auxiliary Training Objective for Improving Multi-Relational Graph Representationscited by 37
  30. 2024KICGPT: Large Language Model with Knowledge in Context for Knowledge Graph Completioncited by 36
  31. 2024Knowledge Graph Large Language Model (KG-LLM) for Link Predictioncited by 36
  32. 2023Neural Graph Reasoning: Complex Logical Query Answering Meets Graph Databasescited by 35
  33. 2021ChronoR: Rotation Based Temporal Knowledge Graph Embeddingcited by 34
  34. 2021Prototypical Representation Learning for Relation Extractioncited by 33
  35. 2023Dipping PLMs Sauce: Bridging Structure and Text for Effective Knowledge Graph Completion via Conditional Soft Promptingcited by 33
  36. 2022Knowledge Is Flat: A Seq2Seq Generative Framework for Various Knowledge Graph Completioncited by 32
  37. 2021Meta-Knowledge Transfer for Inductive Knowledge Graph Embeddingcited by 31
  38. 2021Knowledge-Rich Self-Supervision for Biomedical Entity Linkingcited by 31

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