Research Data Leeds Repository

Citation

Richard-Bollans, Adam and Gómez Álvarez, Lucía and Bennett, Brandon and Cohn, Anthony G. (2019) Investigating the Dimensions of Spatial Language: A Preliminary Study. University of Leeds. [Dataset] https://doi.org/10.5518/620

Dataset description

In order to collect rich data on spatial prepositions, we have created a framework for gathering user annotations in 3D virtual environments. The framework is built using the Blender 3D modelling software and game engine. The framework initially provides two distinct tasks with which our preliminary study was conducted — a Selection Task and a Description Task. In both tasks, participants are given a first person view of a scene which they can navigate using the mouse and keyboard. In the Selection Task participants are given a preposition on screen and asked to select all figure-ground pairs in the scene which fit the preposition. Once they have selected all pairs they believe to be admissible they are shown another preposition and asked to repeat the process. In our preliminary study, we limited this task to ‘in’, ‘inside’, ‘on’, ‘on top of’, ‘against’, ‘over’, ‘under’, ‘above’ and ‘below’. In the Description Task objects are highlighted and participants are able to type in a spatial description of the object. In our preliminary study we asked participants to give descriptions of the object locations using a definite description, in the format figure + preposition + ground e.g. ‘the guitar by the bookshelf’. We also allowed the use of multiple prepositions if the participant deemed it necessary e.g. ‘the cup on the table near the lamp’. To make the annotations more relevant to our research we asked participants to only use the prepositions in the Selection Task plus ‘to the right of’, ‘to the left of’, ‘in front of’, ‘behind’, ‘near’, ‘next to’, ‘at’. The current dataset is from a session we hosted in one of our computing labs where we invited participants from across the university campus to take part. We asked participants to complete either the Selection Task or Description Task in one of our scenes. Participants were given a brief introduction to the study and instructions on how to complete the given task along with explanations of key terminology. All participants were asked to create annotations for ten minutes. 23 native English speakers participated, of which 13 performed the Selection Task and 10 performed the Description Task

Keywords:	Spatial Prepositions, Spatial Semantics, Human Robot Interaction, Natural Language Processing, Referring Expression Generation
Subjects:	I000 - Computer sciences > I400 - Artificial intelligence
Divisions:	Faculty of Engineering and Physical Sciences > School of Computing
Related resources:	Location Type https://ceur-ws.org/Vol-2455/paper5.pdf Publication http://eprints.whiterose.ac.uk/148335/ Publication https://etheses.whiterose.ac.uk/28893/ Ethesis
License:	Creative Commons Attribution 4.0 International (CC BY 4.0)
Date deposited:	09 Aug 2019 08:39
URI:	https://archive.researchdata.leeds.ac.uk/id/eprint/558
Additional details Additional details Creators or authors: Creators ORCID Other ID Email Primary affiliation Primary affiliation ID Primary affiliation ID type Secondary affiliation Secondary affiliation ID Secondary affiliation ID type Richard-Bollans, Adam https://orcid.org/0000-0003-1980-0107 University of Leeds https://ror.org/024mrxd33 ror Gómez Álvarez, Lucía https://orcid.org/0000-0002-2525-8839 University of Leeds https://ror.org/024mrxd33 ror Bennett, Brandon https://orcid.org/0000-0001-5020-6478 University of Leeds https://ror.org/024mrxd33 ror Cohn, Anthony G. https://orcid.org/0000-0002-7652-8907 University of Leeds https://ror.org/024mrxd33 ror Type of data: Dataset Publication date: 2019 Resource language: English Metadata language: English Research project title: Modelling Spatial Prepositions for Locative Expression Interpretation and Generation Publisher: University of Leeds Contact email: mm15alrb@leeds.ac.uk Last Modified: 25 Jul 2024 10:57

Files

Documentation

ReadMe [2kB] ReadMe [2kB] ReadMe [2kB] Security: Anyone File name: readme.txt Content type: Documentation Description: Readme explaining the files in the dataset Mime-Type: text/plain License: Creative Commons Attribution 4.0 International (CC BY 4.0) File size: 2kB

Data

Collected Data [583kB] Collected Data [583kB] Collected Data [583kB] Security: Anyone File name: Data.zip Content type: Data Description: Contains lists of collected annotations, participant info and data on configurations of each scene Mime-Type: application/zip License: Creative Commons Attribution 4.0 International (CC BY 4.0) File size: 583kB

Used Scenes [404MB] Used Scenes [404MB] Used Scenes [404MB] Security: Anyone File name: Scenes.zip Content type: Data Description: Provides the scenes which were used in the study Mime-Type: application/zip License: Creative Commons Attribution 4.0 International (CC BY 4.0) File size: 404MB

Participant Instructions [206kB] Participant Instructions [206kB] Participant Instructions [206kB] Security: Anyone File name: Instructions.zip Content type: Data Description: Documents which were shown to the participants of the study Mime-Type: application/zip License: Creative Commons Attribution 4.0 International (CC BY 4.0) File size: 206kB

Program

Data collection software [342MB] Data collection software [342MB] Data collection software [342MB] Security: Anyone File name: tool.zip Content type: Program Description: The framework used to create and run the study Mime-Type: application/zip License: Creative Commons Attribution 4.0 International (CC BY 4.0) File size: 342MB