Collecting semantic information for locations in the scenario-based lexical knowledge resource of a text-to-scene conversion system

Abstract. WordsEye is a system for automatically converting a text de-scription of a scene into a 3D image. In converting a text description into a corresponding 3D scene, it is necessary to map objects and locations specified in the text into the actual 3D objects. Individual objects typi-cally correspond to single 3D models, but locations (e.g. a living room) are typically an ensemble of objects. Prototypical mappings from loca-tions to objects and their relations are called location vignettes, which are not present in existing lexical resources. In this paper we propose a new methodology using Amazon’s Mechanical Turk to collect semantic information for location vignettes. Our preliminary results show that this is a promising approach