# Negation and Speculation in NLP: A Survey, Corpora, Methods, and Applications
## 2 Corpora and Annotation Process
### Corpora
#### 2.2.1 English Corpora
collected 36,828 sentences from 400 admission notes and 400 discharge summaries of one month's data, March 2011, from the EMR database of Peking Union Medical College Hospital [46]. This corpus includes data from four biomedical categories: diseases, symptoms, treatments, and laboratory tests. The BioScope corpus guidelines [14] and other Chinese guidelines [43] were adapted to annotate the corpus. Three domain experts formulated the initial draft and then applied the guidelines to a corpus sample to refine them. The outcome of the process is 21,767 negating sentences from the entire corpus. The IAA measure was based on only 80 notes, annotated by two annotators, reaching 0.79 measured by Cohen kappa. German: The German Negation and Speculation Corpus (GNSC) is the first German annotated corpus in the biomedical domain [61]. It consists of eight anonymized discharge summaries containing medical histories and 175 clinical notes from the nephrology domain, which are shorter than discharge summaries. First, the medical terms were automatically pre-annotated using an annotation tool [65], following the UMLS unified coding standards for EHRs, as per the predefined types. Secondly, a human annotator rectified incorrect annotations and classified whether a given finding occurred in a positive, negative, or speculative context. Finally, a linguist revised the annotated sentences to assure the data quality. As a result, for discharge summaries the negative and speculated sentences were 106 and 22 of 1076 sentences, and for clinical notes 337 and 4 of 1158 sentences. The results show that in this corpus speculation rarely arises. Arabic: The BioArabic is the first Arabic corpus annotated with negation and speculation for biomedical Arabic texts [19]. The corpus consists of 10,165 sentences extracted from 70 medical and biological articles collected from the _Iraqi Journal of Biotechnology_, the _Journal of Damascus University for Health Sciences_, and _Biotechnology News_. An expert linguist adapted the annotation guidelines of the BioScope corpus [14] to Arabic biomedical texts. Five linguist annotators performed the annotation according to the guidelines developed, as described in detail in the paper. The expert linguist resolved disagreements arising between the annotators to report 1297 negated sentences and 1376 speculative ones. Unfortunately, the measure of agreement between the annotators was not reported, and the corpus is not readily available online. Spanish: The IULA Clinical Record corpus consists of 3194 sentences extracted from 300 anonymized clinical records from the main hospitals in Barcelona, Spain [9]. These sentences were manually annotated with negation cues and their scope by three linguists, advised by a clinician. [PERSON] et al. used the English annotation guidelines from several domains: BioScope from the biomedical domain, and ConanDoyle-neg from the short stories domain and general concepts [14; 54; 66]. As in the BioScope guidelines, the annotation guidelines include neither the negation cue nor the subject of the record in the scope. After applying these annotation rules to the entire corpus, the team reported 1093 negated sentences. The percentage of sentences that include negation scope, roughly 35%, is relatively high compared with English corpora. The IAA Cohen kappa rates were 0.85 between annotators 1 and 2 or 3 and 0.88 between annotators 2 and 3. The corpus is publicly available with a CC-BY-SA 3.0 license ([[http://eines.iula.upf.edu/brat/](http://eines.iula.upf.edu/brat/)]([http://eines.iula.upf.edu/brat/](http://eines.iula.upf.edu/brat/)) /#/NegationOnCR_IULA/ (accessed on 5 January 2022)). Spanish: UHU-HUVR, a corpus with 276 radiology reports and 328 patients' personal histories (written in free text) obtained from the Virgen del Rocio Hospital in Seville, Spain [62]. It is considered the first Spanish corpus to include affixal negation. [PERSON] et al. adapted the Thyme corpus guidelines to annotate the negation cues and scope, using two domain experts [67].