# NUBES: A Corpus of Negation and Uncertainty in Spanish Clinical Texts

arXiv: https://arxiv.org/abs/2004.01092 · HTML: https://mlsanity.com/paper/2004.01092/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 2 Apr 2020.

## Built on by (most cited first, 4 of 4)

- [Neural Natural Language Processing for Unstructured Data in Electronic Health Records: a Review](https://mlsanity.com/paper/2107.02975/) (2021)
- [Few-shot learning for medical text: A systematic review](https://mlsanity.com/paper/2204.14081/) (2022)
- [Possible or Definite? A Benchmark for Evaluating Diagnostic Uncertainty Preservation in Clinical Text](https://mlsanity.com/paper/2606.18471/) (2026)
- [A Survey of Spanish Clinical Language Models](https://mlsanity.com/paper/2308.02199/) (2023)

## Abstract (arXiv)

This paper introduces the first version of the NUBes corpus (Negation and Uncertainty annotations in Biomedical texts in Spanish). The corpus is part of an on-going research and currently consists of 29,682 sentences obtained from anonymised health records annotated with negation and uncertainty. The article includes an exhaustive comparison with similar corpora in Spanish, and presents the main annotation and design decisions. Additionally, we perform preliminary experiments using deep learning algorithms to validate the annotated dataset. As far as we know, NUBes is the largest publicly available corpus for negation in Spanish and the first that also incorporates the annotation of speculation cues, scopes, and events.