Applying the Closed World Assumption to SUMO-based FOL Ontologies for Effective Commonsense Reasoning

TL;DR

This paper demonstrates that applying the Closed World Assumption to SUMO-based first-order logic ontologies significantly enhances reasoning capabilities and accuracy in commonsense reasoning tasks by reducing ambiguity and missing knowledge.

Contribution

It introduces a novel application of the Closed World Assumption to FOL ontologies, improving their practical reasoning performance in commonsense tasks.

Findings

Reasoning under CWA improves ontology competency by over 50%.

Almost 30% of structural knowledge is missing in the current FOL translation.

CWA reduces ambiguity, enabling more accurate commonsense question answering.

Abstract

Most commonly, the Open World Assumption is adopted as a standard strategy for the design, construction and use of ontologies. This strategy limits the inferencing capabilities of any system because non-asserted statements (missing knowledge) could be assumed to be alternatively true or false. As we will demonstrate, this is especially the case of first-order logic (FOL) ontologies where non-asserted statements is nowadays one of the main obstacles to its practical application in automated commonsense reasoning tasks. In this paper, we investigate the application of the Closed World Assumption (CWA) to enable a better exploitation of FOL ontologies by using state-of-the-art automated theorem provers. To that end, we explore different CWA formulations for the structural knowledge encoded in a FOL translation of the SUMO ontology, discovering that almost 30 % of the structural knowledge is missing. We evaluate these formulations on a practical experimentation using a very large commonsense benchmark obtained from WordNet through its mapping to SUMO. The results show that the competency of the ontology improves more than 50 % when reasoning under the CWA. Thus, applying the CWA automatically to FOL ontologies reduces their ambiguity and more commonsense questions can be answered