GeospaCy: A tool for extraction and geographical referencing of spatial expressions in textual data

Syed Mehtab alam, Arsevska Elena, Roche Mathieu, Teisseire Maguelonne. 2024. GeospaCy: A tool for extraction and geographical referencing of spatial expressions in textual data. In : Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics: System demonstrations. EACL. Kerrville : Association for Computational Linguistics, 115-122. ISBN 979-8-89176-091-2 Conference of the European Chapter of the Association for Computational Linguistics (EACL 2024). 18, Saint Julian, Malte, 17 Mars 2024/22 Mars 2024.

https://aclanthology.org/events/eacl-2024/#2024eacl-demo

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Résumé : Spatial information in text enables to understand the geographical context and relationships within text for better decision-making across various domains such as disease surveillance, disaster management and other locationbased services. Therefore, it is crucial to understand the precise geographical context for location-sensitive applications. In response to this necessity, we introduce the GeospaCy software tool, designed for the extraction and georeferencing of spatial information present in textual data. GeospaCy fulfils two primary objectives: 1) Geoparsing, which involves extracting spatial expressions, encompassing place names and associated spatial relations within the text data, and 2) Geocoding, which facilitates the assignment of geographical coordinates to the spatial expressions extracted during the Geoparsing task. Geoparsing is evaluated with a disease news article dataset consisting of event information, whereas a qualitative evaluation of geographical coordinates (polygons/geometries) of spatial expressions is performed by end-users for Geocoding task.

Mots-clés libres : Text Mining, GeoParsing, Geocoding, Spatial entities, Natural Language Processing, One Health, Epidemic intelligence, PADI‐web, Event-based surveillance

Agences de financement européennes : European Commission

Programme de financement européen : H2020

Projets sur financement : (EU) MOnitoring Outbreak events for Disease surveillance in a data science context

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