Publication Details |
| Category | Text Publication |
| Reference Category | Book chapters |
| DOI | 10.18653/v1/2024.climatenlp-1.7 |
Licence  |
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| Title (Primary) | Using LLMs to build a database of climate extreme impacts |
| Title (Secondary) | Proceedings of the 1st Workshop on Natural Language Processing Meets Climate Change (ClimateNLP 2024), Bangkok, Thailand, August 16, 2024 |
| Author | Li, N.; Zahra, S.; de Brito, M.M.; Flynn, C.M.; Görnerup, O.; Worou, K.; Kurfalı, M.; Meng, C.; Thiery, W.; Zscheischler, J.
; Messori, G.; Nivre, J. |
| Publisher | Stammbach, D.; Ni, J.; Schimanski, T.; Dutia, K.; Singh, A.; Bingler, J.; Christiaen, C.; Kushwaha, N.; Muccione, V.; Vaghefi, S.A.; Leippold, M. |
| Year | 2024 |
| Department | SUSOZ; CER |
| Page From | 93 |
| Page To | 110 |
| Language | englisch |
| Topic | T5 Future Landscapes |
| Abstract | To better understand how extreme climate,events impact society, we need to increase the,availability of accurate and comprehensive in-,formation about these impacts. We propose a,method for building large-scale databases of,climate extreme impacts from online textual,sources, using LLMs for information extraction,in combination with more traditional NLP tech-,niques to improve accuracy and consistency.,We evaluate the method against a small bench-,mark database created by human experts and,find that extraction accuracy varies for different,types of information. We compare three differ-,ent LLMs and find that, while the commercial,GPT-4 model gives the best performance over-,all, the open-source models Mistral and Mixtral,are competitive for some types of information. |
| Persistent UFZ Identifier | https://www.ufz.de/index.php?en=20939&ufzPublicationIdentifier=29522 |
| Li, N., Zahra, S., de Brito, M.M., Flynn, C.M., Görnerup, O., Worou, K., Kurfalı, M., Meng, C., Thiery, W., Zscheischler, J., Messori, G., Nivre, J. (2024): Using LLMs to build a database of climate extreme impacts In: Stammbach, D., Ni, J., Schimanski, T., Dutia, K., Singh, A., Bingler, J., Christiaen, C., Kushwaha, N., Muccione, V., Vaghefi, S.A., Leippold, M. (eds.) Proceedings of the 1st Workshop on Natural Language Processing Meets Climate Change (ClimateNLP 2024), Bangkok, Thailand, August 16, 2024 Association for Computational Linguistics, Kerrville, p. 93 - 110 10.18653/v1/2024.climatenlp-1.7 |
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