1. Akbik, A., Bergmann, T., Blythe, D., Rasul, K., Schweter, S., Vollgraf, R.: FLAIR: an easy-to-use framework for state-of-the-art NLP. In: Proceedings of the 2019 Conference of the North American Chapter of the Association for Computational Linguistics (demonstrations), pp. 54–59 (2019)
2. Batista, D.: nervaluate Python module for evaluating Named Entity Recognition (NER) models as defined in the SemEval 2013 9.1 task (2020). https://pypi.org/project/nervaluate/
3. Bodenreider, O.: The unified medical language system (UMLS): integrating biomedical terminology. Nucleic Acids Res. 32(suppl_1), D267–D270 (2004)
4. Conneau, A., et al.: Unsupervised cross-lingual representation learning at scale. In: Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics, pp. 8440–8451. Association for Computational Linguistics (2020). https://doi.org/10.18653/v1/2020.acl-main.747, https://aclanthology.org/2020.acl-main.747
5. Institute of Endocrinology: List of abbreviations – Institute of Endocrinology — endo.cz (2009). https://www.endo.cz/files/download/seznam-zkratek.pdf. Accessed 19 Oct 2023