Temporal expressions are all those words that refer to temporality. Their detection or extraction is a complex
task, since it depends on the domain of the text, the language and the way they are written. Their study in
Spanish and more specifically in the clinical domain is scarce, mainly due to the lack of annotated corpora.
In this paper we propose the use of large language models to address the task, comparing the performance of
five models of different characteristics. After a process of experimentation and fine tuning, a new model
called RoBERTime is created for the detection of temporal expressions in Spanish, especially focused in the
clinical domain. This model is publicly available. RoBERTime achieves state-ofthe-art results in the E3C and
Timebank corpora, being the first public model for the detection of temporal expressions in Spanish specialized
in the clinical domain.