Ontological scaffolding for ontology-free representations of complex situations

titleOntological scaffolding for ontology-free representations of complex situations
start_date2024/04/10
schedule16h-17h
onlineno
location_infosur Zoom
summaryWe use natural language to convey information about situations: things that happen or stuff that is true. This ability is supported by systematic relationships between the way we conceptualize situations and the way we describe them. These systematic relationships in turn underwrite inferences that go beyond what one strictly says in describing a situation. The question that motivates this talk is how to design systems that correctly capture the inferences we draw about situations on the basis of their descriptions. Classical approaches to this question–exemplified in their modern form by graph-based representations, such Abstract Meaning Representation–attempt to capture the situation conceptualization associated with a description using a symbolic situation ontology and to draw inferences on the basis of rules stated over that ontology. An increasingly popular alternative to such ontology-factored approaches are ontology-free approaches, which attempt to directly represent inferences about a situation as natural language strings associated with a situation description, thereby bypassing the problem of engineering a situation ontology entirely. I discuss the benefits and drawbacks of these two approaches and present two case studies in synthesizing them that focus specifically on how best to capture inferences about complex situations–i.e. situations, like building a house, that themselves may be composed of subsituations, like laying the house’s foundations, framing the house, etc. I argue that we should ultimately strive for ontology-free representations but that the challenges inherent to reasoning about complex situations highlight the persistent benefits of situation ontologies in providing representational scaffolding for the construction of such representations.
responsiblesBernard