Richard-Bollans, A orcid.org/0000-0003-1980-0107, Gómez Álvarez, L and Cohn, AG orcid.org/0000-0002-7652-8907 (2020) Categorisation, Typicality & Object-Specific Features in Spatial Referring Expressions. In: Proceedings of the Third International Workshop on Spatial Language Understanding. Third International Workshop on Spatial Language Understanding (SpLU 2020), 19 Nov 2020, Online. Association for Computational Linguistics , pp. 39-49.
Abstract
Various accounts of cognition and semantic representations have highlighted that, for some concepts, different factors may influence category and typicality judgements. In particular, some features may be more salient in categorisation tasks while other features are more salient when assessing typicality. In this paper we explore the extent to which this is the case for English spatial prepositions and discuss the implications for pragmatic strategies and semantic models. We hypothesise that object-specific features — related to object properties and affordances — are more salient in categorisation, while geometric and physical relationships between objects are more salient in typicality judgements. In order to test this hypothesis we conducted a study using virtual environments to collect both category and typicality judgements in 3D scenes. Based on the collected data we cannot verify the hypothesis and conclude that object-specific features appear to be salient in both category and typicality judgements, further evidencing the need to include these types of features in semantic models.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2020 Association for Computational Linguistics. This is an open access article under the terms of the Creative Commons Attribution 4.0 International (CC BY 4.0) (https://creativecommons.org/licenses/by/4.0/) |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Engineering & Physical Sciences (Leeds) > School of Computing (Leeds) |
Funding Information: | Funder Grant number EU - European Union 825619 Alan Turing Institute No ref given |
Depositing User: | Symplectic Publications |
Date Deposited: | 19 Oct 2020 13:57 |
Last Modified: | 27 Apr 2021 10:32 |
Status: | Published |
Publisher: | Association for Computational Linguistics |
Identification Number: | 10.18653/v1/2020.splu-1.5 |
Related URLs: | |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:166748 |