Commonsense Reasoning Using WordNet and SUMO: a Detailed Analysis
This work provides incremental analysis for researchers in AI and knowledge representation to enhance commonsense reasoning frameworks.
The paper tackled the problem of assessing the quality of a commonsense reasoning benchmark derived from WordNet and SUMO, identifying issues such as knowledge misalignments and mapping errors to improve resource exploitation.
We describe a detailed analysis of a sample of large benchmark of commonsense reasoning problems that has been automatically obtained from WordNet, SUMO and their mapping. The objective is to provide a better assessment of the quality of both the benchmark and the involved knowledge resources for advanced commonsense reasoning tasks. By means of this analysis, we are able to detect some knowledge misalignments, mapping errors and lack of knowledge and resources. Our final objective is the extraction of some guidelines towards a better exploitation of this commonsense knowledge framework by the improvement of the included resources.