Enhancing Location Entity Recognition in Spanish Medical Texts by Leveraging Domain Language Models and Data Augmentation

Resumen

This work focuses on the automatic recognition of location entities in Spanish clinical reports, using the MEDDOPLACE challenge (IberLEF 2023) as the experimental framework. We evaluated both general-domain pre-trained models and biomedical-specific models. Furthermore, we explored data augmentation techniques via back-translation and LLM-based paraphrase generation. Our results outperform previous state-of-the-art approaches, demonstrating the effectiveness of combining these data augmentation strategies with pre-trained clinical domain models.