  In this paper, we report on the practical application of a novel approach for
validating the knowledge of WordNet using Adimen-SUMO. In particular, this
paper focuses on cross-checking the WordNet meronymy relations against the
knowledge encoded in Adimen-SUMO. Our validation approach tests a large set of
competency questions (CQs), which are derived (semi)-automatically from the
knowledge encoded in WordNet, SUMO and their mapping, by applying efficient
first-order logic automated theorem provers. Unfortunately, despite of being
created manually, these knowledge resources are not free of errors and
discrepancies. In consequence, some of the resulting CQs are not plausible
according to the knowledge included in Adimen-SUMO. Thus, first we focus on
(semi)-automatically improving the alignment between these knowledge resources,
and second, we perform a minimal set of corrections in the ontology. Our aim is
to minimize the manual effort required for an extensive validation process. We
report on the strategies followed, the changes made, the effort needed and its
impact when validating the WordNet meronymy relations using improved versions
of the mapping and the ontology. Based on the new results, we discuss the
implications of the appropriate corrections and the need of future
enhancements.
