@inproceedings{mehtab-alam-etal-2024-geospacy,
title = "{G}eospa{C}y: A tool for extraction and geographical referencing of spatial expressions in textual data",
author = "Mehtab Alam, Syed and
Arsevska, Elena and
Roche, Mathieu and
Teisseire, Maguelonne",
editor = "Aletras, Nikolaos and
De Clercq, Orphee",
booktitle = "Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations",
month = mar,
year = "2024",
address = "St. Julians, Malta",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.eacl-demo.13",
pages = "115--126",
abstract = "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 location based 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.",
}
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%0 Conference Proceedings
%T GeospaCy: A tool for extraction and geographical referencing of spatial expressions in textual data
%A Mehtab Alam, Syed
%A Arsevska, Elena
%A Roche, Mathieu
%A Teisseire, Maguelonne
%Y Aletras, Nikolaos
%Y De Clercq, Orphee
%S Proceedings of the 18th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations
%D 2024
%8 March
%I Association for Computational Linguistics
%C St. Julians, Malta
%F mehtab-alam-etal-2024-geospacy
%X 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 location based 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.
%U https://aclanthology.org/2024.eacl-demo.13
%P 115-126
Markdown (Informal)
[GeospaCy: A tool for extraction and geographical referencing of spatial expressions in textual data](https://aclanthology.org/2024.eacl-demo.13) (Mehtab Alam et al., EACL 2024)
ACL