NUBes: A Corpus of Negation and Uncertainty in Spanish Clinical Texts

Salvador Lima Lopez, Naiara Perez, Montse Cuadros, German Rigau


Abstract
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 available corpora for negation in Spanish and the first that also incorporates the annotation of speculation cues, scopes, and events.
Anthology ID:
2020.lrec-1.708
Volume:
Proceedings of the 12th Language Resources and Evaluation Conference
Month:
May
Year:
2020
Address:
Marseille, France
Venues:
COLING | LREC
SIG:
Publisher:
European Language Resources Association
Note:
Pages:
5772–5781
Language:
English
URL:
https://www.aclweb.org/anthology/2020.lrec-1.708
DOI:
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PDF:
http://aclanthology.lst.uni-saarland.de/2020.lrec-1.708.pdf