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RGCL-WLV at SemEval-2019 Task 12: Toponym Detection
Plum, Alistair Ranasinghe, Tharindu Calleja, Pablo Orasan, Constantin Mitkov, Ruslan
Plum, Alistair
Ranasinghe, Tharindu
Calleja, Pablo
Orasan, Constantin
Mitkov, Ruslan
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2019-06-07
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Abstract
This article describes the system submitted by the RGCL-WLV team to the SemEval 2019 Task 12: Toponym resolution in scientific papers. The system detects toponyms using a bootstrapped machine learning (ML) approach which classifies names identified using gazetteers extracted from the GeoNames geographical database. The paper evaluates the performance of several ML classifiers, as well as how the gazetteers influence the accuracy of the system. Several runs were submitted. The highest precision achieved for one of the submissions was 89%, albeit it at a relatively low recall of 49%.
Citation
Alistair Plum, Tharindu Ranasinghe, Pablo Calleja, Constantin Orăsan and Ruslan Mitkov (2019) RGCL-WLV at SemEval-2019 Task 12: Toponym Detection. In Proceedings of the 13th International Workshop on Semantic Evaluation (SemEval-2019), pp. 1297–1301, Minneapolis, Minnesota, USA, June 6–7
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en
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9781950737062