Skip to main navigation Skip to search Skip to main content

Commonsense Ontology Micropatterns

Research output: Chapter in Book/Report/Conference proceedingConference contribution

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 ontology design patterns (ODPs) into design libraries, which are programmatically queryable. However, a major bottleneck to large-scale deployment of MOMo is the (to-date) limited availability of ready-to-use ODPs. At the same time, Large Language Models (LLMs) 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 ODPs 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.
Original languageEnglish
Title of host publicationNeural-Symbolic Learning and Reasoning - 18th International Conference, NeSy 2024, Proceedings
EditorsTarek R. Besold, Artur d’Avila Garcez, Ernesto Jimenez-Ruiz, Pranava Madhyastha, Benedikt Wagner, Roberto Confalonieri
PublisherSpringer Science and Business Media Deutschland GmbH
Pages51-59
Number of pages9
ISBN (Print)9783031711695
DOIs
StatePublished - 2024
Event18th International Conference on Neural-Symbolic Learning and Reasoning, NeSy 2024 - Barcelona, Spain
Duration: Sep 9 2024Sep 12 2024

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume14980 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference18th International Conference on Neural-Symbolic Learning and Reasoning, NeSy 2024
Country/TerritorySpain
CityBarcelona
Period9/9/249/12/24

ASJC Scopus Subject Areas

  • Theoretical Computer Science
  • General Computer Science

Cite this