# Ontology-to-tools compilation for executable semantic constraint enforcement in LLM agents

arXiv: https://arxiv.org/abs/2602.03439 · HTML: https://mlsanity.com/paper/2602.03439/

## Key facts

- Cited by 3 papers in the map (data through 14 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.

## Placed in

- LLM agents and tool use / [Web, search, and research agents](https://mlsanity.com/agents/web-search-and-research-agents/)

## Builds on (most cited first, 8 of 8)

- [ReAct: Synergizing Reasoning and Acting in Language Models](https://mlsanity.com/paper/2210.03629/) (2022)
- [Toolformer: Language Models Can Teach Themselves to Use Tools](https://mlsanity.com/paper/2302.04761/) (2023)
- [AutoGen: Enabling Next-Gen LLM Applications via Multi-Agent Conversation](https://mlsanity.com/paper/2308.08155/) (2023)
- [KGGen: Extracting Knowledge Graphs from Plain Text with Language Models](https://mlsanity.com/paper/2502.09956/) (2025)
- [From human experts to machines: An LLM supported approach to ontology and knowledge graph construction](https://mlsanity.com/paper/2403.08345/) (2024)
- [AutoSchemaKG: Autonomous Knowledge Graph Construction through Dynamic Schema Induction from Web-Scale Corpora](https://mlsanity.com/paper/2505.23628/) (2025)
- [ODKE+: Ontology-Guided Open-Domain Knowledge Extraction with LLMs](https://mlsanity.com/paper/2509.04696/) (2025)
- [RELATE: Relation Extraction in Biomedical Abstracts with LLMs and Ontology Constraints](https://mlsanity.com/paper/2509.19057/) (2025)

## Built on by (most cited first, 3 of 3)

- [El Agente Gr'afico: A Semantic Execution Runtime for Scientific Agents](https://mlsanity.com/paper/2602.17902/) (2026)
- [Graph Engineering in the Era of LLM Agents: From Individual Intelligence to System Intelligence](https://mlsanity.com/paper/2608.21156/) (2026)
- [LLM Agents Factory: Retrieval of Domain-Specific LLM Agents](https://mlsanity.com/paper/2608.09934/) (2026)

## 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.