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What Do You Mean You're in Trafalgar Square? Comparing Distance Thresholds for Geospatial Prepositions

Authors Niloofar Aflaki , Kristin Stock , Christopher B. Jones , Hans Guesgen, Jeremy Morley, Yukio Fukuzawa

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Author Details

Niloofar Aflaki
  • Massey Geoinformatics Collaboratory, Massey University, Auckland, New Zealand
Kristin Stock
  • Massey Geoinformatics Collaboratory, Massey University, Auckland, New Zealand
Christopher B. Jones
  • School of Computer Science and Informatics, Cardiff University, UK
Hans Guesgen
  • Massey Geoinformatics Collaboratory, Massey University, Auckland, New Zealand
Jeremy Morley
  • Ordnance Survey, Southampton, UK
Yukio Fukuzawa
  • School of Natural and Computational Sciences, Massey University, Auckland, New Zealand

Funding

This work is partly funded through by an Ordnance Survey (UK) PhD scholarship.

Cite AsGet BibTex

Niloofar Aflaki, Kristin Stock, Christopher B. Jones, Hans Guesgen, Jeremy Morley, and Yukio Fukuzawa. What Do You Mean You're in Trafalgar Square? Comparing Distance Thresholds for Geospatial Prepositions. In 15th International Conference on Spatial Information Theory (COSIT 2022). Leibniz International Proceedings in Informatics (LIPIcs), Volume 240, pp. 1:1-1:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2022)
https://doi.org/10.4230/LIPIcs.COSIT.2022.1

Abstract

Natural language location descriptions frequently describe object locations relative to other objects (the house near the river). Geospatial prepositions (e.g.near) are a key element of these descriptions, and the distances associated with proximity, adjacency and topological prepositions are thought to depend on the context of a specific scene. When referring to the context, we include consideration of properties of the relatum such as its feature type, size and associated image schema. In this paper, we extract spatial descriptions from the Google search engine for nine prepositions across three locations, compare their acceptance thresholds (the distances at which different prepositions are acceptable), and study variations in different contexts using cumulative graphs and scatter plots. Our results show that adjacency prepositions next to and adjacent to are used for a large range of distances, in contrast to beside; and that topological prepositions in, at and on can all be used to indicate proximity as well as containment and collocation. We also found that reference object image schema influences the selection of geospatial prepositions such as near and in.

Subject Classification

ACM Subject Classification
  • Computing methodologies → Natural language processing
Keywords
  • contextual factors
  • spatial descriptions
  • acceptance model
  • spatial template
  • applicability model
  • geospatial prepositions

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