RGCL-WLV at SemEval-2019 task 12: Toponym detection

1Citations
Citations of this article
81Readers
Mendeley users who have this article in their library.

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%.

Cite

CITATION STYLE

APA

Plum, A., Ranasinghe, T., Calleja, P., Orăsan, C., & Mitkov, R. (2019). RGCL-WLV at SemEval-2019 task 12: Toponym detection. In NAACL HLT 2019 - International Workshop on Semantic Evaluation, SemEval 2019, Proceedings of the 13th Workshop (pp. 1297–1301). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/s19-2228

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free