Goto

Collaborating Authors

 Masolo, Claudio


DOLCE: A Descriptive Ontology for Linguistic and Cognitive Engineering

arXiv.org Artificial Intelligence

DOLCE, the first top-level (foundational) ontology to be axiomatized, has remained stable for twenty years and today is broadly used in a variety of domains. DOLCE is inspired by cognitive and linguistic considerations and aims to model a commonsense view of reality, like the one human beings exploit in everyday life in areas as diverse as socio-technical systems, manufacturing, financial transactions and cultural heritage. DOLCE clearly lists the ontological choices it is based upon, relies on philosophical principles, is richly formalized, and is built according to well-established ontological methodologies, e.g. OntoClean. Because of these features, it has inspired most of the existing top-level ontologies and has been used to develop or improve standards and public domain resources (e.g. CIDOC CRM, DBpedia and WordNet). Being a foundational ontology, DOLCE is not directly concerned with domain knowledge. Its purpose is to provide the general categories and relations needed to give a coherent view of reality, to integrate domain knowledge, and to mediate across domains. In these 20 years DOLCE has shown that applied ontologies can be stable and that interoperability across reference and domain ontologies is a reality. This paper briefly introduces the ontology and shows how to use it on a few modeling cases.


The Counting Problem in the Light of Role Kinds

AAAI Conferences

Starting from a general characterization of roles, we focus on the ways in which roles are specified, we examine the formal constraints on their definitions, and propose definitional schemas motivating different kinds of roles. This classification, in addition to clarify the notion of role itself, helps us to reconsider the two standard solutions that have been proposed for the famous counting problem, and to suggest that a third mixed approach may be considered.


Sweetening WORDNET with DOLCE

AI Magazine

In this article, we discuss the general problems related to the semantic interpretation of WORDNET taxonomy in light of rigorous ontological principles inspired by the philosophical tradition. Then we introduce the DOLCE upper-level ontology, which is inspired by such principles but with a clear orientation toward language and cognition. We report the results of an experimental effort to align WORDNET's upper level with DOLCE. We suggest that such alignment could lead to an "ontologically sweetened" WORDNET, meant to be conceptually more rigorous, cognitively transparent, and efficiently exploitable in several applications.


Sweetening WORDNET with DOLCE

AI Magazine

Despite its original intended use, which was very different, WORDNET is used more and more today as an ontology, where the hyponym relation between word senses is interpreted as a subsumption relation between concepts. In this article, we discuss the general problems related to the semantic interpretation of WORDNET taxonomy in light of rigorous ontological principles inspired by the philosophical tradition. Then we introduce the DOLCE upper-level ontology, which is inspired by such principles but with a clear orientation toward language and cognition. We report the results of an experimental effort to align WORDNET's upper level with DOLCE. We suggest that such alignment could lead to an "ontologically sweetened" WORDNET, meant to be conceptually more rigorous, cognitively transparent, and efficiently exploitable in several applications.