Disaster Storylines and Knowledge Graphs from Global News with Large Language Models and Retrieval-Augmented Generation
Abstract We present a dataset of over 3,000 global disaster events from 2014 to 2024, derived from the Emergency Events Database (EM-DAT). Events are extracted from news using a pipeline combining Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG) for semantic extraction. The corp...
Αποθηκεύτηκε σε:
| Κύριοι συγγραφείς: | , , , , , , , |
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| Μορφή: | Artigo |
| Γλώσσα: | Inglês |
| Έκδοση: |
Nature Portfolio
2026-03-01
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| Σειρά: | Scientific Data |
| Διαθέσιμο Online: | https://doi.org/10.1038/s41597-026-07036-2 |
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