Detecting the geospatialness of prepositions from natural language text

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.

Keywords

spatial language, natural language processing, geospatial language

Citation

Radke M, Das P, Stock K, Jones CB. (2019). Detecting the geospatialness of prepositions from natural language text. Timpf S, Schlieder C, Kattenbeck M, Ludwig B, Stewart K. Leibniz International Proceedings in Informatics Lipics. (pp. 11:1-11:8). Schloss Dagstuhl – Leibniz-Zentrum für Informatik.

URI

https://mro.massey.ac.nz/handle/10179/73131

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