  Semantic annotation is fundamental to deal with large-scale lexical
information, mapping the information to an enumerable set of categories over
which rules and algorithms can be applied, and foundational ontology classes
can be used as a formal set of categories for such tasks. A previous alignment
between WordNet noun synsets and DOLCE provided a starting point for
ontology-based annotation, but in NLP tasks verbs are also of substantial
importance. This work presents an extension to the WordNet-DOLCE noun mapping,
aligning verbs according to their links to nouns denoting perdurants,
transferring to the verb the DOLCE class assigned to the noun that best
represents that verb's occurrence. To evaluate the usefulness of this resource,
we implemented a foundational ontology-based semantic annotation framework,
that assigns a high-level foundational category to each word or phrase in a
text, and compared it to a similar annotation tool, obtaining an increase of
9.05% in accuracy.
