mlsanityData to 7 Oct 2026

Faithiful Embeddings for EL++ Knowledge Bases

arXiv 2201.09919 ↗First posted 24 Jan 2022cs.AI cs.LG cs.LOcited by 25

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Abstract (arXiv)

Recently, increasing efforts are put into learning continual representations for symbolic knowledge bases (KBs). However, these approaches either only embed the data-level knowledge (ABox) or suffer from inherent limitations when dealing with concept-level knowledge (TBox), i.e., they cannot faithfully model the logical structure present in the KBs. We present BoxEL, a geometric KB embedding approach that allows for better capturing the logical structure (i.e., ABox and TBox axioms) in the description logic EL++. BoxEL models concepts in a KB as axis-parallel boxes that are suitable for modeling concept intersection, entities as points inside boxes, and relations between concepts/entities as affine transformations. We show theoretical guarantees (soundness) of BoxEL for preserving logical structure. Namely, the learned model of BoxEL embedding with loss 0 is a (logical) model of the KB. Experimental results on (plausible) subsumption reasonings and a real-world application for protein-protein prediction show that BoxEL outperforms traditional knowledge graph embedding methods as well as state-of-the-art EL++ embedding approaches.

Key facts. Cited by 25 papers in the map (data through 7 Oct 2026). Builds on 15 of its 43 references that are in the map. First posted on arXiv 24 Jan 2022.

Builds on

15 of 43 references.

References · 15

  1. 2014Adam: A Method for Stochastic Optimizationcited by 36,960
  2. 2014Embedding Entities and Relations for Learning and Inference in Knowledge Basescited by 929
  3. 2016Complex Embeddings for Simple Link Predictioncited by 897
  4. 2017Convolutional 2D Knowledge Graph Embeddingscited by 729
  5. 2020Query2box: Reasoning over Knowledge Graphs in Vector Space using Box Embeddingscited by 169
  6. 2020Beta Embeddings for Multi-Hop Logical Reasoning in Knowledge Graphscited by 128
  7. 2020BoxE: A Box Embedding Model for Knowledge Base Completioncited by 105
  8. 2017Analogical Inference for Multi-Relational Embeddingscited by 69
  9. 2018Probabilistic Embedding of Knowledge Graphs with Box Lattice Measurescited by 64
  10. 2019EL Embeddings: Geometric construction of models for the Description Logic EL ++cited by 48
  11. 2020Improving Local Identifiability in Probabilistic Box Embeddingscited by 35
  12. 2018OPA2Vec: combining formal and informal content of biomedical ontologies to improve similarity-based predictioncited by 25
3 more
  1. 2018From Knowledge Graph Embedding to Ontology Embedding? An Analysis of the Compatibility between Vector Space Representations and Rulescited by 19
  2. 2018Onto2Vec: joint vector-based representation of biological entities and their ontology-based annotationscited by 18
  3. 2017Towards Statistical Reasoning in Description Logics over Finite Domains (Full Version)cited by 3

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2023: 7; 2024: 11; 2025: 1; 2026: 6.

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  1. 2024Concept-Based Explanations in Computer Vision: Where Are We and Where Could We Go?cited by 17
  2. 2023Shrinking Embeddings for Hyper-Relational Knowledge Graphscited by 12
  3. 2024Ontology Embedding: A Survey of Methods, Applications and Resourcescited by 12
  4. 2023HiPrompt: Few-Shot Biomedical Knowledge Fusion via Hierarchy-Oriented Promptingcited by 11
  5. 2023Geometric Relational Embeddings: A Surveycited by 8
  6. 2024Capturing Knowledge Graphs and Rules with Octagon Embeddingscited by 5
  7. 2024Generating SROI^- Ontologies via Knowledge Graph Query Embedding Learningcited by 5
  8. 2024TransBox: EL++-closed Ontology Embeddingcited by 5
  9. 2024Approximating Probabilistic Inference in Statistical EL with Knowledge Graph Embeddingscited by 4
  10. 2024DAGE: DAG Query Answering via Relational Combinator with Logical Constraintscited by 4
  11. 2025Language Models as Ontology Encoderscited by 4
  12. 2023Towards Semantically Enriched Embeddings for Knowledge Graph Completioncited by 3
13 more
  1. 2024A Self-matching Training Method with Annotation Embedding Models for Ontology Subsumption Predictioncited by 2
  2. 2023Biomedical Knowledge Graph Embeddings with Negative Statementscited by 1
  3. 2023Neuro-Symbolic RDF and Description Logic Reasoners: The State-Of-The-Art and Challengescited by 1
  4. 2024Enhancing Geometric Ontology Embeddings for EL++ with Negative Sampling and Deductive Closure Filteringcited by 1
  5. 2024Building Trustworthy AI: Transparent AI Systems via Large Language Models, Ontologies, and Logical Reasoning (TranspNet)cited by 1
  6. 2026Graph Neural Network based Hierarchy-Aware Embeddings of Knowledge Graphs: Applications to Yeast Phenotype Predictioncited by 1
  7. 2026Scalable Uncertainty Reasoning in Knowledge Graphscited by 1
  8. 2023Lattice-preserving ALC ontology embeddings with saturationcited by 0
  9. 2024DELE: Deductive EL++ Embeddings for Knowledge Base Completioncited by 0
  10. 2026NeurOWL: An LLM-Based Neural-symbolic Framework for Incomplete OWL Ontology Reasoningcited by 0
  11. 2026Neuro-symbolic learning over OWL 2 DL via consequence-based compilation to differentiable circuitscited by 0
  12. 2026Hierarchy-Aware Semantic Losses for Knowledge Graph Link Predictioncited by 0
  13. 2026A hierarchy of faithfulness criteria for knowledge base completioncited by 0