License: Creative Commons Attribution 3.0 Unported license (CC BY 3.0)
When quoting this document, please refer to the following
DOI: 10.4230/LIPIcs.COSIT.2019.11
URN: urn:nbn:de:0030-drops-111033
URL: http://dagstuhl.sunsite.rwth-aachen.de/volltexte/2019/11103/
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Radke, Mansi ; Das, Prarthana ; Stock, Kristin ; Jones, Christopher B.

Detecting the Geospatialness of Prepositions from Natural Language Text (Short Paper)

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Abstract

There is increasing interest in detecting the presence of geospatial locative expressions that include spatial relation terms such as near or within <some distance>. Being able to do so provides a foundation for interpreting relative descriptions of location and for building corpora that facilitate the development of methods for spatial relation extraction and interpretation. Here we evaluate the use of a spatial role labelling procedure to distinguish geospatial uses of prepositions from other spatial and non-spatial uses and experiment with the use of additional machine learning features to improve the quality of detection of geospatial prepositions. An annotated corpus of nearly 2000 instances of preposition usage was created for training and testing the classifiers.

BibTeX - Entry

@InProceedings{radke_et_al:LIPIcs:2019:11103,
  author =	{Mansi Radke and Prarthana Das and Kristin Stock and Christopher B. Jones},
  title =	{{Detecting the Geospatialness of Prepositions from Natural Language Text (Short Paper)}},
  booktitle =	{14th International Conference on Spatial Information Theory (COSIT 2019)},
  pages =	{11:1--11:8},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-115-3},
  ISSN =	{1868-8969},
  year =	{2019},
  volume =	{142},
  editor =	{Sabine Timpf and Christoph Schlieder and Markus Kattenbeck and Bernd Ludwig and Kathleen Stewart},
  publisher =	{Schloss Dagstuhl--Leibniz-Zentrum fuer Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{http://drops.dagstuhl.de/opus/volltexte/2019/11103},
  URN =		{urn:nbn:de:0030-drops-111033},
  doi =		{10.4230/LIPIcs.COSIT.2019.11},
  annote =	{Keywords: spatial language, natural language processing, geospatial language}
}

Keywords: spatial language, natural language processing, geospatial language
Collection: 14th International Conference on Spatial Information Theory (COSIT 2019)
Issue Date: 2019
Date of publication: 03.09.2019

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