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Collecting Spatial Information for Locations in a Text-to-Scene Conversion System

Rouhizadeh, Masoud; Bauer, Daniel; Coyne, Robert Eric; Rambow, Owen C.; Sproat, Richard

We investigate using Amazon Mechanical Turk (AMT) for building a low-level description corpus and populating VigNet, a comprehensive semantic resource that we will use in a text-to-scene generation system. To depict a picture of a location, VigNet should contain the knowledge about the typical objects in that location and the arrangements of those objects. Such information is mostly common-sense knowledge that is taken for granted by human beings and is not stated in existing lexical resources and in text corpora. In this paper we focus on collecting objects of locations using AMT. Our results show that it is a promising approach.


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More About This Work

Academic Units
Computer Science
Center for Computational Learning Systems
CoSLI-2 (Computational Models for Spatial Languages) at CogSci 2011
Published Here
August 2, 2013