Ontology-to-tools compilation for executable semantic constraint enforcement in LLM agents
On the map: LLM agents and tool use → Web, search, and research agents
Abstract (arXiv)
We introduce ontology-to-tools compilation as a proof-of-principle mechanism for coupling large language models (LLMs) with formal domain knowledge. Within The World Avatar (TWA), ontological specifications are compiled into executable tool interfaces that LLM-based agents must use to create and modify knowledge graph instances, enforcing semantic constraints during generation rather than through post-hoc validation. Extending TWA's semantic agent composition framework, the Model Context Protocol (MCP) and associated agents are integral components of the knowledge graph ecosystem, enabling structured interaction between generative models, symbolic constraints, and external resources. An agent-based workflow translates ontologies into ontology-aware tools and iteratively applies them to extract, validate, and repair structured knowledge from unstructured scientific text. Using metal-organic polyhedra synthesis literature as an illustrative case, we show how executable ontological semantics can guide LLM behaviour and reduce manual schema and prompt engineering, establishing a general paradigm for embedding formal knowledge into generative systems.
Key facts. Cited by 3 papers in the map (data through 7 Oct 2026). Placed in Web, search, and research agents, one of 16 directions in LLM agents and tool use. Builds on 8 of its 69 references that are in the map. First posted on arXiv 3 Feb 2026.
Builds on
8 of 69 references.
References · 8
- 2022ReAct: Synergizing Reasoning and Acting in Language Modelscited by 8,355
- 2023Toolformer: Language Models Can Teach Themselves to Use Toolscited by 4,072
- 2023AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversationcited by 1,906
- 2025KGGen: Extracting Knowledge Graphs from Plain Text with Language Modelscited by 49
- 2024From human experts to machines: An LLM supported approach to ontology and knowledge graph constructioncited by 40
- 2025AutoSchemaKG: Autonomous Knowledge Graph Construction through Dynamic Schema Induction from Web-Scale Corporacited by 23
- 2025ODKE+: Ontology-Guided Open-Domain Knowledge Extraction with LLMscited by 3
- 2025RELATE: Relation Extraction in Biomedical Abstracts with LLMs and Ontology Constraintscited by 3
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Citing papers per year: 2026: 3.
3 papers.
Similar, not cited
Close in wording, no citation either way
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- 2026Toward Effective and Reliable LLM Agents via Dynamic Ontology
- 2025LLM-empowered knowledge graph construction: A survey
- 2023Agent-OM: Leveraging LLM Agents for Ontology Matching
- 2026Toward Formalizing LLM-Based Agent Designs through Structural Context Modeling and Semantic Dynamics Analysis
- 2026Automatic Ontology Construction Using LLMs as an External Layer of Memory, Verification, and Planning for Hybrid Intelligent Systems
- 2026The Semantic Training Gap: Ontology-Grounded Tool Architectures for Industrial AI Agent Systems
- 2026WFM: Wiki Foundation Model for Complex Agentic Reasoning