pro-team at LLMs4OL 2026 Tasks Flagship and Reuse: Retrieval-Augmented Generation and Vocabulary-Constrained Filtering for Ontology Learning

arXiv:2608.27101 · cs.AI · Submitted 2026-08-27 · Read on arXiv

cs.AI

Submitted: 2026-08-27

Updated: 2026-09-01

Code: https://github.com/shivam07041/team-pro-integration_OntoLearner_Submission

Terminology

• Ontology — 137× in this paper · explained in 2 episodes
• Ontology Learning — 54× in this paper
• Benchmark — 8× in this paper · explained in 2 episodes
• Retrieval-Augmented Generation — 7× in this paper
• RAG — 6× in this paper · explained in 3 episodes
• Consistency — 4× in this paper · explained in 3 episodes
• Transformer — 4× in this paper · explained in 2 episodes
• Accuracy — 3× in this paper · explained in 1 episode
• Alignment — 3× in this paper · explained in 1 episode
• Embeddings — 3× in this paper · explained in 2 episodes
• Feature Engineering — 3× in this paper · explained in 3 episodes
• Hallucination — 3× in this paper · explained in 4 episodes
• Retrieval-Augmented Generation (RAG) — 3× in this paper · explained in 16 episodes
• Semantic Similarity — 3× in this paper · explained in 2 episodes
• Ablation — 2× in this paper · explained in 1 episode
• Ablation Studies — 2× in this paper · explained in 1 episode
• Axioms — 2× in this paper · explained in 2 episodes
• Clustering — 2× in this paper · explained in 2 episodes
• Contextual Understanding — 2× in this paper · explained in 2 episodes
• Generative AI — 2× in this paper · explained in 2 episodes
• Generative Model — 2× in this paper · explained in 2 episodes
• Generative Models — 2× in this paper · explained in 2 episodes
• Grounding — 2× in this paper · explained in 3 episodes
• Knowledge Graph — 2× in this paper · explained in 7 episodes
• Knowledge graphs — 2× in this paper · explained in 2 episodes
• Adaptability — 1× in this paper · explained in 1 episode
• Cosine Similarity — 1× in this paper · explained in 3 episodes
• Fine-Tuning — 1× in this paper · explained in 5 episodes
• Large Language Model (LLM) — 1× in this paper · explained in 3 episodes
• Large Language Models (LLMs) — 1× in this paper · explained in 6 episodes
• Prompt Engineering — 1× in this paper · explained in 4 episodes
• Representation Learning — 1× in this paper · explained in 2 episodes
• Robustness — 1× in this paper · explained in 5 episodes
• Tokenization — 1× in this paper · explained in 2 episodes

Sources

• Ontology Learning with LLMs: A Benchmark Study on Axiom Identification
• Heterogeneous LLM Methods for Ontology Learning (Few-Shot Prompting, Ensemble Typing, and Attention-Based Taxonomies)

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