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Spatial descriptions on a functional-geometric spectrum: the location of objects

Conference paper
Authors Simon Dobnik
Mehdi Ghanimifard
Published in Spatial Cognition XII: Proceedings of the 12th International Conference, Spatial Cognition 2020, Riga, Latvia
ISSN 0302-9743
Publisher Springer Nature Switzerland AG
Place of publication Cham, Switzerland
Publication year 2020
Published at Department of Philosophy, Linguistics and Theory of Science
Language en
Keywords spatial descriptions, geometric, functional, corpus, image captions, computational model
Subject categories Linguistics, Cognitive science, Computational linguistics


Experimental research on spatial descriptions shows that their semantics are dependent on several modalities, among others (i) a geometric representation of space ("where", geometric knowledge) and (ii) dynamic kinematic routines between objects that are related ("what", functional knowledge). In this paper we examine whether geometric and functional bias of spatial relations is also reflected in large corpora of images and their corresponding descriptions. In particular, we examine whether the variation in object locations in the usage of a relation is a predictor of that relation’s functional or geometric bias. Previous experimental psycho-linguistic work has examined the bias of some spatial relations, however our corpus-based computational analysis allows us to examine the bias of spatial relations and verbs beyond those that have been tested experimentally. Our findings have also implications for building computational image descriptions systems as we demonstrate what kind of representational knowledge is required to model spatial relations contained in them.

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