Update README.md

README.md

@@ -39,7 +39,7 @@ The model achieves the following results on the test set (when trained with the
 
 This model adapts the pre-trained model [bsc-bio-ehr-es](https://huggingface.co/PlanTL-GOB-ES/bsc-bio-ehr-es), presented in [Pio Carriño et al. (2022)](https://aclanthology.org/2022.bionlp-1.19/). 
 It is fine-tuned to conduct medical named entity recognition on Spanish texts about clinical trials. 
-The model is fine-tuned on the [NUBEs corpus (Lima et al. 2020)](https://aclanthology.org/2020.lrec-1.708/) and on the [CT-EBM-ES corpus (Campillos-Llanos et al. 2021)](https://bmcmedinformdecismak.biomedcentral.com/articles/10.1186/s12911-021-01395-z).
+The model is fine-tuned on the [NUBEs corpus (Lima et al. 2020)](https://aclanthology.org/2020.lrec-1.708/) and on the [CT-EBM-SP corpus (Campillos-Llanos et al. 2021)](https://bmcmedinformdecismak.biomedcentral.com/articles/10.1186/s12911-021-01395-z).
 
 ## Intended uses & limitations
 
@@ -72,7 +72,7 @@ It is a collection of 1200 texts about clinical trials studies and clinical tria
 - 500 abstracts from journals published under a Creative Commons license, e.g. available in PubMed or the Scientific Electronic Library Online (SciELO)
 - 700 clinical trials announcements published in the European Clinical Trials Register and Repositorio Español de Estudios Clínicos
 
-If you use the CT-EBM-ES resource, please, cite as follows:
+If you use the CT-EBM-SP resource, please, cite as follows:
 
 ```
 @article{campillosetal-midm2021,