mlsanityData to 14 Oct 2026

LLMs4OL: Large Language Models for Ontology Learning

arXiv 2307.16648 ↗First posted 31 Jul 2023cs.AI cs.CL cs.ITcited by 77

Not on the map. Why?

Abstract (arXiv)

We propose the LLMs4OL approach, which utilizes Large Language Models (LLMs) for Ontology Learning (OL). LLMs have shown significant advancements in natural language processing, demonstrating their ability to capture complex language patterns in different knowledge domains. Our LLMs4OL paradigm investigates the following hypothesis: textitCan LLMs effectively apply their language pattern capturing capability to OL, which involves automatically extracting and structuring knowledge from natural language text? To test this hypothesis, we conduct a comprehensive evaluation using the zero-shot prompting method. We evaluate nine different LLM model families for three main OL tasks: term typing, taxonomy discovery, and extraction of non-taxonomic relations. Additionally, the evaluations encompass diverse genres of ontological knowledge, including lexicosemantic knowledge in WordNet, geographical knowledge in GeoNames, and medical knowledge in UMLS.

Key facts. Cited by 77 papers in the map (data through 14 Oct 2026). Builds on 30 of its 72 references that are in the map. First posted on arXiv 31 Jul 2023.

Builds on

30 of 72 references.

References · 30

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2020Language Models are Few-Shot Learnerscited by 32,419
  3. 2023LLaMA: Open and Efficient Foundation Language Modelscited by 14,132
  4. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,459
  5. 2019BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehensioncited by 5,893
  6. 2022Large Language Models are Zero-Shot Reasonerscited by 4,374
  7. 2021Prefix-Tuning: Optimizing Continuous Prompts for Generationcited by 3,915
  8. 2021The Power of Scale for Parameter-Efficient Prompt Tuningcited by 3,795
  9. 2021Finetuned Language Models Are Zero-Shot Learnerscited by 3,780
  10. 2023Tree of Thoughts: Deliberate Problem Solving with Large Language Modelscited by 3,211
  11. 2022Emergent Abilities of Large Language Modelscited by 2,512
  12. 2018Deep contextualized word representationscited by 2,290
18 more
  1. 2021Pre-train, Prompt, and Predict: A Systematic Survey of Prompting Methods in Natural Language Processingcited by 2,234
  2. 2022Beyond the Imitation Game: Quantifying and extrapolating the capabilities of language modelscited by 1,998
  3. 2022BLOOM: A 176B-Parameter Open-Access Multilingual Language Modelcited by 1,984
  4. 2019Language Models as Knowledge Bases?cited by 1,936
  5. 2019Transformer-XL: Attentive Language Models Beyond a Fixed-Length Contextcited by 1,850
  6. 2016ConceptNet 5.5: An Open Multilingual Graph of General Knowledgecited by 1,067
  7. 2020Domain-Specific Language Model Pretraining for Biomedical Natural Language Processingcited by 1,009
  8. 2019How Can We Know What Language Models Know?cited by 959
  9. 2023The Flan Collection: Designing Data and Methods for Effective Instruction Tuningcited by 739
  10. 2017Convolutional 2D Knowledge Graph Embeddingscited by 730
  11. 2022Decomposed Prompting: A Modular Approach for Solving Complex Taskscited by 558
  12. 2017Zero-Shot Relation Extraction via Reading Comprehensioncited by 426
  13. 2020How Context Affects Language Models' Factual Predictionscited by 181
  14. 2021Template-Based Named Entity Recognition Using BARTcited by 153
  15. 2022Discovering Latent Concepts Learned in BERTcited by 56
  16. 2022Analyzing Encoded Concepts in Transformer Language Modelscited by 38
  17. 2019Simple Applications of BERT for Ad Hoc Document Retrievalcited by 34
  18. 2023Transformer models: an introduction and catalogcited by 21

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 1; 2024: 26; 2025: 19; 2026: 31.

77 papers.

Sort:

By area:

  1. 2024From human experts to machines: An LLM supported approach to ontology and knowledge graph constructioncited by 40
  2. 2023Agent-OM: Leveraging LLM Agents for Ontology Matchingcited by 27
  3. 2025Ontology Generation using Large Language Modelscited by 25
  4. 2024OG-RAG: Ontology-Grounded Retrieval-Augmented Generation For Large Language Modelscited by 23
  5. 2025AutoSchemaKG: Autonomous Knowledge Graph Construction through Dynamic Schema Induction from Web-Scale Corporacited by 23
  6. 2025LLM-empowered knowledge graph construction: A surveycited by 21
  7. 2025On Verifiable Legal Reasoning: A Multi-Agent Framework with Formalized Knowledge Representationscited by 18
  8. 2024OntoChat: a Framework for Conversational Ontology Engineering using Language Modelscited by 15
  9. 2024Research Trends for the Interplay between Large Language Models and Knowledge Graphscited by 15
  10. 2024End-to-End Ontology Learning with Large Language Modelscited by 13
  11. 2024LLMs4Life: Large Language Models for Ontology Learning in Life Sciencescited by 12
  12. 2024Do LLMs Really Adapt to Domains? An Ontology Learning Perspectivecited by 11
38 more
  1. 2024Towards Next-Generation Urban Decision Support Systems through AI-Powered Construction of Scientific Ontology using Large Language Models -- A Case in Optimizing Intermodal Freight Transportationcited by 10
  2. 2024Large Language Models for Scholarly Ontology Generation: An Extensive Analysis in the Engineering Fieldcited by 10
  3. 2024A Fine-tuning Enhanced RAG System with Quantized Influence Measure as AI Judgecited by 9
  4. 2024GenAI-powered Multi-Agent Paradigm for Smart Urban Mobility: Opportunities and Challenges for Integrating Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) with Intelligent Transportation Systemscited by 9
  5. 2024Accelerating Knowledge Graph and Ontology Engineering with Large Language Modelscited by 9
  6. 2024LLMs4OL 2024 Overview: The 1st Large Language Models for Ontology Learning Challengecited by 8
  7. 2024Generalizable and Scalable Multistage Biomedical Concept Normalization Leveraging Large Language Modelscited by 7
  8. 2024Decision support system for Forest fire management using Ontology with Big Data and LLMscited by 6
  9. 2026ErrorMap and ErrorAtlas: Charting the Failure Landscape of Large Language Modelscited by 6
  10. 2024Comparative Study of Domain Driven Terms Extraction Using Large Language Modelscited by 5
  11. 2024On the Use of Large Language Models to Generate Capability Ontologiescited by 5
  12. 2024Refining Wikidata Taxonomy using Large Language Modelscited by 5
  13. 2024Toward a Method to Generate Capability Ontologies from Natural Language Descriptionscited by 4
  14. 2024Human Evaluation of Procedural Knowledge Graph Extraction from Text with Large Language Modelscited by 4
  15. 2025Mining for Species, Locations, Habitats, and Ecosystems from Scientific Papers in Invasion Biology: A Large-Scale Exploratory Study with Large Language Modelscited by 4
  16. 2025Retrieval-Augmented Generation of Ontologies from Relational Databasescited by 4
  17. 2025Ontology Learning with LLMs: A Benchmark Study on Axiom Identificationcited by 4
  18. 2024OAEI-LLM: A Benchmark Dataset for Understanding Large Language Model Hallucinations in Ontology Matchingcited by 3
  19. 2025Heterogeneous LLM Methods for Ontology Learning (Few-Shot Prompting, Ensemble Typing, and Attention-Based Taxonomies)cited by 3
  20. 2025Addressing Longstanding Challenges in Cognitive Science with Language Modelscited by 3
  21. 2026Large Language Model for OWL Proofscited by 3
  22. 2026Ontology-Constrained Neural Reasoning in Enterprise Agentic Systems: A Neurosymbolic Architecture for Domain-Grounded AI Agentscited by 3
  23. 2026Rashomon Memory: Towards Argumentation-Driven Retrieval for Multi-Perspective Agent Memorycited by 3
  24. 2026OntoLearner: A Modular Python Library for Ontology Learning with Large Language Modelscited by 3
  25. 2024Prompt-Time Ontology-Driven Symbolic Knowledge Capture with Large Language Modelscited by 2
  26. 2025Leveraging Large Language Models for Generating Research Topic Ontologies: A Multi-Disciplinary Studycited by 2
  27. 2025MetaGraph: A Large-Scale Meta-Analysis of GenAI in Financial NLP (2022-2025)cited by 2
  28. 2026Open Ontologies: Tool-Augmented Ontology Engineering with Stable Matching Alignmentcited by 2
  29. 2026K12-KGraph: A Curriculum-Aligned Knowledge Graph for Benchmarking and Training Educational LLMscited by 2
  30. 2024DSTI at LLMs4OL 2024 Task A: Intrinsic versus extrinsic knowledge for type classificationcited by 1
  31. 2024Data-driven Coreference-based Ontology Buildingcited by 1
  32. 2025Large Language Model-Based Agents for Automated Research Reproducibility: An Exploratory Study in Alzheimer's Diseasecited by 1
  33. 2025RELRaE: LLM-Based Relationship Extraction, Labelling, Refinement, and Evaluationcited by 1
  34. 2025Minimizing Hyperbolic Embedding Distortion with LLM-Guided Hierarchy Restructuringcited by 1
  35. 2026Structured Decomposition for LLM Reasoning: Cross-Domain Validation and Semantic Web Integrationcited by 1
  36. 2026Towards Automated Ontology Generation from Unstructured Text: A Multi-Agent LLM Approachcited by 1
  37. 2026Ontology-Amplified Distillation and Contextuality Auditing for Sovereign Enterprise Language Models: A Combined Proof-of-Mechanism and Negative-Results Method Studycited by 1
  38. 2026SINT-Flow: Schema Integration using Large Language Model Workflowscited by 1

50 most cited of 77 All 77 (JSON)