RACCOON: A Retrieval-Augmented Generation Approach for Location Coordinate Capture from News Articles
Year: 2025
Type: conference-paper
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.
Authors: Jonathan Lin, Aditya Joshi, Hye-young Paik, Tri Dung Doung, Deepti Gurdasani
Institution: UNSW Sydney
Language: English
Topic: Topic Modeling
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W4410637840