将领域知识编译为可执行工具，让大模型生成时自动遵守语义约束。
Ontology-to-tools compilation for executable semantic constraint enforcement in LLM agents
- 把本体转化为可调用工具，强制大模型按规则生成知识。
- 在金属有机多面体文献中验证，减少人工调参与模式设计。
- 适合需要高精度知识生成的科研与工程场景。
我们提出本体到工具的编译机制，作为将大语言模型（LLMs）与形式化领域知识结合的示范性方法。在《世界化身》（TWA）系统中，本体规范被编译为可执行工具接口，基于大模型的代理必须使用这些接口来创建和修改知识图谱实例，从而在生成过程中而非事后验证阶段实施语义约束。扩展了TWA的语义代理组合框架，模型上下文协议（MCP）及配套代理是知识图谱生态的核心组件，支持生成模型、符号约束与外部资源之间的结构化交互。一种基于代理的工作流将本体转化为具备本体感知能力的工具，并迭代应用于从非结构化科学文本中提取、验证和修复结构化知识。以金属有机多面体合成文献为例，展示了可执行的本体语义如何引导大模型行为，减少手动模式与架构设计，建立了一种将形式化知识嵌入生成系统的一般范式。
原文摘要 · Abstract (English)
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.
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