RACCOON: A Retrieval-Augmented Generation Approach for Location Coordinate Capture from News Articles

Geocoding involves automatic extraction of location coordinates of incidents reported in news articles, and can be used for epidemic intelligence or disaster management.This paper introduces Retrieval-Augmented Coordinate Capture Of Online News articles (RACCOON), an open-source 1 geocoding approach that extracts geolocations from news articles.RACCOON uses a retrievalaugmented generation (RAG) approach where candidate locations and associated information are retrieved in the form of context from a location database, and a prompt containing the retrieved context, location mentions and news articles is fed to an LLM to generate the location coordinates.Our evaluation on three datasets, two underlying LLMs, three baselines and several ablation tests based on the components of RACCOON demonstrate the utility of RACCOON.To the best of our knowledge, RACCOON is the first RAG-based approach for geocoding using pre-trained LLMs.

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Published
2025-05-08
DOI
https://doi.org/10.1145/3701716.3715501
Citations
3
Primary Topic
Data Management and Algorithms
Type
article
Field-Weighted Citation Impact
4.46
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RACCOON: A Retrieval-Augmented Generation Approach for Location Coordinate Capture from News Articles

Hye-Young Paik, Tri Dung Duong, Aditya Joshi, Deepti Gurdasani et al.
3 citations
Data Management and Algorithms
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article

RACCOON: A Retrieval-Augmented Generation Approach for Location Coordinate Capture from News Articles

Hye-Young Paik, Tri Dung Duong, Aditya Joshi, Deepti Gurdasani, Jonathan Lin
article en
3 citations

Abstract

Geocoding involves automatic extraction of location coordinates of incidents reported in news articles, and can be used for epidemic intelligence or disaster management.This paper introduces Retrieval-Augmented Coordinate Capture Of Online News articles (RACCOON), an open-source 1 geocoding approach that extracts geolocations from news articles.RACCOON uses a retrievalaugmented generation (RAG) approach where candidate locations and associated information are retrieved in the form of context from a location database, and a prompt containing the retrieved context, location mentions and news articles is fed to an LLM to generate the location coordinates.Our evaluation on three datasets, two underlying LLMs, three baselines and several ablation tests based on the components of RACCOON demonstrate the utility of RACCOON.To the best of our knowledge, RACCOON is the first RAG-based approach for geocoding using pre-trained LLMs.

UNSW Sydney (AU)
Openalex Percentile: Top 6%
Data Management and Algorithms
4.46
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