In this paper we present on-going work on annotating negation in Spanish clinical documents. A corpus of anamnesis and radiology reports has been annotated by two domain expert annotators with negation markers and negated events. The Dice coefficient for inter-annotator agreement is higher than 0.94 for negation markers and higher than 0.72 for negated events. The corpus will be publicly released when the annotation process is finished, constituting the first corpus annotated with negation for Spanish clinical reports available for the NLP community.

This paper presents a freely available resource for research on handling negation and speculation in review texts. The SFU Review Corpus, consisting of 400 documents of movie, book, and consumer product reviews, was annotated at the token level with negative and speculative keywords and at the sentence level with their linguistic scope. We report statistics on corpus size and the consistency of annotations. The annotated corpus will be useful in many applications, such as document mining and sentiment analysis.