Transformer based named entity recognition for place name extraction from unstructured text

Berragan, Cillian ORCID: 0000-0003-2198-2245, 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.

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Official URL: http://dx.doi.org/10.1080/13658816.2022.2133125

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 F1 score metric. Our best performing model achieves an F1 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:	26 Nov 2023 19:20
DOI:	10.1080/13658816.2022.2133125
Open Access URL:	https://doi.org/10.1080/13658816.2022.2133125
Related URLs:	Author Publisher
URI:	https://livrepository.liverpool.ac.uk/id/eprint/3165936