Berragan, Cillian, Singleton, Alex, Calafiore, Alessia and Morley, Jeremy
(2023)
Transformer based named entity recognition for place name extraction from unstructured text
INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE, 37 (4).
pp. 747-766.
ISSN 1365-8816, 1362-3087
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Abstract
Place names embedded in online natural language text present a useful source of geographic information. Despite this, many methods for the extraction of place names from text use pre-trained models that were not explicitly designed for this task. Our paper builds five custom-built Named Entity Recognition (NER) models and evaluates them against three popular pre-built models for place name extraction. The models are evaluated using a set of manually annotated Wikipedia articles with reference to the F<inf>1</inf> score metric. Our best performing model achieves an F<inf>1</inf> score of 0.939 compared with 0.730 for the best performing pre-built model. Our model is then used to extract all place names from Wikipedia articles in Great Britain, demonstrating the ability to more accurately capture unknown place names from volunteered sources of online geographic information.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | Named entity recognition, volunteered geographic information, natural language processing, place name extraction |
| Depositing User: | Symplectic Admin |
| Date Deposited: | 01 Nov 2022 16:25 |
| Last Modified: | 16 Jun 2026 09:57 |
| DOI: | 10.1080/13658816.2022.2133125 |
| Open Access URL: | https://doi.org/10.1080/13658816.2022.2133125 |
| Related Websites: | |
| URI: | https://livrepository.liverpool.ac.uk/id/eprint/3165936 |
| Disclaimer: | The University of Liverpool is not responsible for content contained on other websites from links within repository metadata. Please contact us if you notice anything that appears incorrect or inappropriate. |
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