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Found 9 papers, 1 papers with code
Towards Cross-checking WordNet and SUMO Using Meronymy
We describe the practical application of a black-box testing methodology for the validation of the knowledge encoded in WordNet, SUMO and their mapping by using automated theorem provers.
This is not a Dataset: A Large Negation Benchmark to Challenge Large Language Models
We have used our dataset with the largest available open LLMs in a zero-shot approach to grasp their generalization and inference capability and we have also fine-tuned some of the models to assess whether the understanding of negation can be trained.
Commonsense Reasoning Using WordNet and SUMO: a Detailed Analysis
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.
Applying the Closed World Assumption to SUMO-based FOL Ontologies for Effective Commonsense Reasoning
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.
Validating WordNet Meronymy Relations using Adimen-SUMO
In this paper, we report on the practical application of a novel approach for validating the knowledge of WordNet using Adimen-SUMO.
Black-box Testing of First-Order Logic Ontologies Using WordNet
Applying different quality criteria, our testing proposal enables a successful evaluation of a) the competency of several translations of SUMO into FOL and b) the performance of various automated ATPs.
Automatic White-Box Testing of First-Order Logic Ontologies
Our proposal enables the detection of defects and serves to certify the grade of suitability --for reasoning purposes-- of every axiom.
Evaluating the Competency of a First-Order Ontology
We report on the results of evaluating the competency of a first-order ontology for its use with automated theorem provers (ATPs).
Improving the Competency of First-Order Ontologies
We introduce a new framework to evaluate and improve first-order (FO) ontologies using automated theorem provers (ATPs) on the basis of competency questions (CQs).
