We present Open Ontologies, an open-source ontology engineering system implemented in Rust that integrates LLM-driven construction with formal OWL reasoning and ontology alignment via the Model Context Protocol. Our primary finding is that stable 1-to-1 matching is the dominant factor in ontology alignment quality: on the OAEI Anatomy track, it achieves F1 = 0.832 (P = 0.963, R = 0.733), competitive with state-of-the-art systems and exceeding all in precision. Ablation across five weight configurations shows that signal weights are irrelevant when stable matching is applied (F1 varies by less than 0.004), while removing stable matching drops F1 to 0.728. On the Conference track, the same method achieves F1 = 0.438. On tool-augmented ontology interaction, we find a surprising result: an LLM reading a raw OWL file (F1 = 0.323) performs worse than the same LLM with no file at all (F1 = 0.431), while structured MCP tool access achieves F1 = 0.717. This demonstrates that tool structure provides a qualitatively different mode of access that the LLM cannot replicate by reading raw syntax. The system ships as a single binary under the MIT licence.

翻译：我们提出了开放本体论——一个用Rust实现的开源本体工程系统，它通过模型上下文协议将基于大语言模型的构建与形式化OWL推理及本体对齐相结合。核心发现是稳定的一对一匹配是影响本体对齐质量的关键因素：在OAEI解剖学数据集上，该方法取得了F1=0.832（精确率=0.963，召回率=0.733），与现有最佳系统性能相当，且在所有系统中精确率最高。通过五种权重配置的消融实验表明，当使用稳定匹配时，信号权重无关紧要（F1差异小于0.004），而移除稳定匹配后F1降至0.728。在会议数据集上，相同方法取得的F1为0.438。在工具增强的本体交互方面，我们得到了一项出人意料的结果：直接读取原始OWL文件的大语言模型（F1=0.323）性能甚至低于完全不访问文件的大语言模型（F1=0.431），而通过结构化MCP工具访问时F1达到0.717。这表明工具结构为大语言模型提供了本质上不同的访问模式，这是单纯读取原始语法所无法复现的。该系统以单一可执行文件形式发布，遵循MIT开源协议。