Commonsense Ontology Micropatterns

TL;DR

Commonsense Ontology Micropatterns addresses the need for scalable, ready-to-use ontology design patterns to support Modular Ontology Modeling (MOMo). The authors generate 104 commonsense micropatterns for nouns by prompting large language models and consolidate them into CS-MODL, a fully annotated MODL that is programmatically queryable. This approach enables pattern-based construction and inference within knowledge graphs through MODLs and OPaL annotations, providing a practical open resource to accelerate automated ontology development and transfer/analogy learning. The work lays groundwork for case studies, hierarchical organization of concepts, and richer OWL representations, with future plans to expand noun coverage and enhance documentation and expressivity.

Abstract

The previously introduced Modular Ontology Modeling methodology (MOMo) attempts to mimic the human analogical process by using modular patterns to assemble more complex concepts. To support this, MOMo organizes organizes ontology design patterns into design libraries, which are programmatically queryable, to support accelerated ontology development, for both human and automated processes. However, a major bottleneck to large-scale deployment of MOMo is the (to-date) limited availability of ready-to-use ontology design patterns. At the same time, Large Language Models have quickly become a source of common knowledge and, in some cases, replacing search engines for questions. In this paper, we thus present a collection of 104 ontology design patterns representing often occurring nouns, curated from the common-sense knowledge available in LLMs, organized into a fully-annotated modular ontology design library ready for use with MOMo.

Figures (2)

• Figure 1: The 104 nouns conceptualized into our commonsense micropatterns.
• Figure 2: A graphical schema diagram of the Air ontology