Whether automatically extracted or human generated, open-domain factual knowledge is often available in the form of semantic annotations (., composed-by) that take one or more specific instances (., rhapsody in blue, george gershwin) as their arguments. This paper introduces a method for converting flat sets of instance-level annotations into hierarchically organized, concept-level annotations, which capture not only the broad semantics of the desired arguments (., ‘People’ rather than ‘Locations’), but also the correct level of generality (., ‘Composers’ rather than ‘People’, or ‘Jazz Composers’). The method refrains from encoding features specific to a particular domain or annotation, to ensure.
