mlsanityData to 14 Oct 2026

Language Model Analysis for Ontology Subsumption Inference

arXiv 2302.06761 ↗First posted 14 Feb 2023cs.CL cs.AI cs.LOcited by 25

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Abstract (arXiv)

Investigating whether pre-trained language models (LMs) can function as knowledge bases (KBs) has raised wide research interests recently. However, existing works focus on simple, triple-based, relational KBs, but omit more sophisticated, logic-based, conceptualised KBs such as OWL ontologies. To investigate an LM's knowledge of ontologies, we propose OntoLAMA, a set of inference-based probing tasks and datasets from ontology subsumption axioms involving both atomic and complex concepts. We conduct extensive experiments on ontologies of different domains and scales, and our results demonstrate that LMs encode relatively less background knowledge of Subsumption Inference (SI) than traditional Natural Language Inference (NLI) but can improve on SI significantly when a small number of samples are given. We will open-source our code and datasets.

Key facts. Cited by 25 papers in the map (data through 14 Oct 2026). Builds on 19 of its 47 references that are in the map. First posted on arXiv 14 Feb 2023.

Builds on

19 of 47 references.

References · 19

  1. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,599
  2. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,372
  3. 2013Efficient Estimation of Word Representations in Vector Spacecited by 4,375
  4. 2017A Broad-Coverage Challenge Corpus for Sentence Understanding through Inferencecited by 2,682
  5. 2019Language Models as Knowledge Bases?cited by 1,936
  6. 2020Making Pre-trained Language Models Better Few-shot Learnerscited by 1,256
  7. 2022Diffusion-LM Improves Controllable Text Generationcited by 1,027
  8. 2020Exploiting Cloze Questions for Few Shot Text Classification and Natural Language Inferencecited by 938
  9. 2021Time-Aware Language Models as Temporal Knowledge Basescited by 296
  10. 2021Factual Probing Is [MASK]: Learning vs. Learning to Recallcited by 291
  11. 2022A Review on Language Models as Knowledge Basescited by 157
  12. 2021OpenPrompt: An Open-source Framework for Prompt-learningcited by 148
7 more
  1. 2021Can Language Models be Biomedical Knowledge Bases?cited by 83
  2. 2021Probing Across Time: What Does RoBERTa Know and When?cited by 73
  3. 2021BERTMap: A BERT-based Ontology Alignment Systemcited by 46
  4. 2021Analyzing Commonsense Emergence in Few-shot Knowledge Modelscited by 34
  5. 2022Contextual Semantic Embeddings for Ontology Subsumption Predictioncited by 31
  6. 2022Ontology-enhanced Prompt-tuning for Few-shot Learningcited by 24
  7. 2022Are Prompt-based Models Clueless?cited by 11

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Citing papers per year: 2023: 9; 2024: 6; 2025: 4; 2026: 6.

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  1. 2023Large Language Models and Knowledge Graphs: Opportunities and Challengescited by 71
  2. 2023OLaLa: Ontology Matching with Large Language Modelscited by 35
  3. 2024Language Models as Hierarchy Encoderscited by 28
  4. 2023Emptying the Ocean with a Spoon: Should We Edit Models?cited by 27
  5. 2023Agent-OM: Leveraging LLM Agents for Ontology Matchingcited by 27
  6. 2024Editing Conceptual Knowledge for Large Language Modelscited by 21
  7. 2023DeepOnto: A Python Package for Ontology Engineering with Deep Learningcited by 20
  8. 2023Knowledge Graphs for the Life Sciences: Recent Developments, Challenges and Opportunitiescited by 10
  9. 2023Ontology Enrichment from Texts: A Biomedical Dataset for Concept Discovery and Placementcited by 7
  10. 2025The LLM Bottleneck: Why Open-Source Vision LLMs Struggle with Hierarchical Visual Recognitioncited by 7
  11. 2025OntoURL: A Benchmark for Evaluating Large Language Models on Symbolic Ontological Understanding, Reasoning and Learningcited by 6
  12. 2024Ontology Completion with Natural Language Inference and Concept Embeddings: An Analysiscited by 4
13 more
  1. 2024Do LLMs Dream of Ontologies?cited by 3
  2. 2024A Language Model based Framework for New Concept Placement in Ontologiescited by 3
  3. 2026Large Language Model for OWL Proofscited by 3
  4. 2026Hierarchical Text Classification with LLM-Refined Taxonomiescited by 2
  5. 2026How Do Large Language Models Learn Concepts During Continual Pre-Training?cited by 1
  6. 2026From Subsumption to Satisfiability: LLM-Assisted Active Learning for OWL Ontologiescited by 1
  7. 2023What can knowledge graph alignment gain with Neuro-Symbolic learning approaches?cited by 0
  8. 2023Transformers in the Service of Description Logic-based Contextscited by 0
  9. 2024Ontological Relations from Word Embeddingscited by 0
  10. 2025Disentangling concept semantics via multilingual averaging in Sparse Autoencoderscited by 0
  11. 2025Hierarchical Retrieval with Out-Of-Vocabulary Queries: A Case Study on SNOMED CTcited by 0
  12. 2026NeurOWL: An LLM-Based Neural-symbolic Framework for Incomplete OWL Ontology Reasoningcited by 0
  13. 2026Ontology-Grounded, Reasoner-Verified Benchmarks for Evaluating LLM Reasoning in Scientific AIcited by 0