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Where is the News? Improving Toponym Identification and Differentiation in Online News

Title: Where is the News? Improving Toponym Identification and Differentiation in Online News
Authors: Shingleton, Joseph; Basiri, Ana
Publication Year: 2024
Collection: University of Glasgow: Enlighten - Publications
Subject Terms: QA75 Electronic computers. Computer science
Description: Understanding the geographical context of unstructured textual data is a key challenge in information extraction. In many applications, however, simple identification of toponyms is insufficient and can often lead to ambiguities in the extracted information. One such application is in the geolocation of online news - where a single article may mention multiple locations, with only one location referring to the article’s subject. In this paper, we present a transformer based model, trained to identify the subject toponyms of news articles. Further, our model identifies likely parents of the subject toponym, potentially helping to improve later geolocation tasks. Our model is able to identify the subject of anarticle with an F1-score of 0.760 when tested on a human-tagged test dataset.
Document Type: conference object
File Description: text
Language: English
Relation: https://eprints.gla.ac.uk/321323/3/321323.pdf; Shingleton, Joseph ORCID logoorcid:0000-0002-1628-3231 and Basiri, Ana ORCID logoorcid:0000-0002-2399-1797 (2024) Where is the News? Improving Toponym Identification and Differentiation in Online News. In: Second International Workshop on Geographic Information Retreival, Glasgow, 24 March 2024, pp. 34-42.
Availability: https://eprints.gla.ac.uk/321323/; https://eprints.gla.ac.uk/321323/3/321323.pdf; https://ceur-ws.org/Vol-3683/
Rights: cc_by_4
Accession Number: edsbas.22AD5010
Database: BASE