RACCOON: A Retrieval-Augmented Generation Approach for Location Coordinate Capture from News Articles
On the map: Retrieval-augmented generation → RAG for recommendation
Abstract (arXiv)
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 geocoding approach that extracts geolocations from news articles. RACCOON uses a retrieval-augmented 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.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in RAG for recommendation, one of 15 directions in Retrieval-augmented generation. Builds on 5 of its 13 references that are in the map. First posted on arXiv 20 Jan 2025.
Builds on
5 of 13 references.
References · 5
- 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,160
- 2018A Pragmatic Guide to Geoparsing Evaluationcited by 17
- 2023Improving Toponym Resolution with Better Candidate Generation, Transformer-based Reranking, and Two-Stage Resolutioncited by 7
- 2019Survey of Text-based Epidemic Intelligence: A Computational Linguistic Perspectivecited by 6
- 2023Mordecai 3: A Neural Geoparser and Event Geocodercited by 6
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- 2024Quantifying Geospatial in the Common Crawl Corpus
- 2025Geolocation with Real Human Gameplay Data: A Large-Scale Dataset and Human-Like Reasoning Framework
- 2025Spatial-RAG: Spatial Retrieval Augmented Generation for Real-World Geospatial Reasoning Questions
- 2026Much of Geospatial Web Search Is Beyond Traditional GIS
- 2025RAG for Geoscience: What We Expect, Gaps and Opportunities