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

Authors Mansi Radke , Prarthana Das, Kristin Stock , Christopher B. Jones



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Author Details

Mansi Radke
  • Computer Science and Engineering Department, Visvesvaraya National Institute of Technology, Nagpur, India
Prarthana Das
  • Computer Science and Engineering Department, Visvesvaraya National Institute of Technology, Nagpur, India
Kristin Stock
  • Massey Geoinformatics Collaboratory, Massey University, Auckland, New Zealand
Christopher B. Jones
  • School of Computer Science and Informatics, Cardiff University, Cardiff, United Kingdom

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Mansi Radke, Prarthana Das, Kristin Stock, and Christopher B. Jones. Detecting the Geospatialness of Prepositions from Natural Language Text (Short Paper). In 14th International Conference on Spatial Information Theory (COSIT 2019). Leibniz International Proceedings in Informatics (LIPIcs), Volume 142, pp. 11:1-11:8, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2019)
https://doi.org/10.4230/LIPIcs.COSIT.2019.11

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.

Subject Classification

ACM Subject Classification
  • Computing methodologies → Artificial intelligence
  • Computing methodologies → Natural language processing
Keywords
  • spatial language
  • natural language processing
  • geospatial language

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References

  1. Richard Johansson and Pierre Nugues. LTH: Semantic Structure Extraction using Nonprojective Dependency Trees. In Proceedings of the Fourth International Workshop on Semantic Evaluations (SemEval-2007), pages 227-230. Association for Computational Linguistics, 2007. Google Scholar
  2. Arbaz Khan, Maria Vasardani, and Stephan Winter. Extracting Spatial Information From Place Descriptions. In COMP@ SIGSPATIAL, page 62, 2013. Google Scholar
  3. Parisa Kordjamshidi, Martijn Van Otterlo, and Marie-Francine Moens. Spatial Role Labeling: Towards Extraction of Spatial Relations from Natural Language. ACM Trans. Speech Lang. Process., 8(3):4:1-4:36, December 2011. Google Scholar
  4. Ken Litkowski and Orin Hargraves. SemEval-2007 Task 06: Word-sense Disambiguation of Prepositions. In Proceedings of the 4th International Workshop on Semantic Evaluations, SemEval '07, pages 24-29, Stroudsburg, PA, USA, 2007. Association for Computational Linguistics. Google Scholar
  5. Fei Liu. Automatic identification of locative expressions from informal text. Masters by Coursework & Shorter thesis, University of Melbourne, Melbourne, Australia, 2013. URL: http://minerva-access.unimelb.edu.au/handle/11343/38520.
  6. Fei Liu, Maria Vasardani, and Timothy Baldwin. Automatic Identification of Locative Expressions from Social Media Text: A Comparative Analysis. In Proceedings of the 4th International Workshop on Location and the Web, LocWeb '14, pages 9-16, New York, NY, USA, 2014. ACM. Google Scholar
  7. V.B. Robinson. Individual and multipersonal fuzzy spatial relations acquired using human-machine interaction. Fuzzy Sets and Systems, 113(1):133-145, 2000. Google Scholar
  8. Kristin Stock, Robert C. Pasley, Zoe Gardner, Paul Brindley, Jeremy Morley, and Claudia Cialone. Creating a Corpus of Geospatial Natural Language. In Proceedings of the 11th International Conference on Spatial Information Theory - Volume 8116, pages 279-298. Springer-Verlag New York, Inc., September 2013. Google Scholar
  9. Jan Oliver Wallgrün, Alexander Klippel, and Timothy Baldwin. Building a Corpus of Spatial Relational Expressions Extracted from Web Documents. In Proceedings of the 8th Workshop on Geographic Information Retrieval, GIR '14, pages 6:1-6:8, New York, NY, USA, 2014. ACM. Google Scholar
  10. M. Worboys. Nearness relations in environmental space. International Journal of Geographic Information Science, 15(7):633-651, 2001. Google Scholar
  11. Xiaobai Yao and Jean-Claude Thill. How Far Is Too Far? – A Statistical Approach to Context-contingent Proximity Modeling. Transactions in GIS, 9(2):157-178, 2005. Google Scholar
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