Enhancing Toponym Resolution with Fine-Tuned LLMs (Llama2)

Kurzfassung

In this study, we investigate the use of mid-sized and open-source large language models to enhance the extraction of geographic information from texts, focusing on toponym resolution. Our approach involves fine-tuning Llama2 (7B) to accurately derive the unambiguous references of toponyms within textual contexts and subsequently assign geo-coordinates using geocoders. The method is evaluated on two challenging datasets featuring 28,342 global toponyms. The findings demonstrate notable performance improvements compared to existing state-of-the-art methods while maintaining computational efficiency.