# Negation and Speculation in NLP: A Survey, Corpora, Methods, and Applications
## 2 Corpora and Annotation Process
### Corpora
#### 2.2.1 English Corpora
The results of the annotation are 1079 negated sentences of the 3065 in the patient histories and 1219 negated sentences of the 5347 in the radiology documents. As observed in the report, the percentage of negated sentences in the histories is relatively high since they are patients' descriptions of clinical conditions, which are not 100% factual,whereas the radiology report gives the radiologists' observations. The IAA measure for the negation scope was 0.72. Spanish: The SFU ReviewSP Negation (NEG) extends the SFU Review corpus [57]; it consists of 400 review documents from domains such as movies, music, and various product reviews, extracted from the Ciao.es website [26]. Each domain contains 25 positive and 25 negative review documents, based on the stars awarded by the reviewer. It is the first Spanish corpus to include events in the annotation and reflect any discontinuous negation cues. Like its English equivalent, the entire corpus was manually annotated with negation cues and their consequent scope and events [40]. Although the Bioscope corpus guidelines had been written for the biomedical domain, for the review domain the authors adapted these guidelines alongside a typology of negation patterns in Spanish [14]. The annotation process was supervised by experts and performed by two trained annotators, who came up with 3022 negated sentences in the 9455 sentences. The IAA kappa coefficient is 0.95 for negated events and 0.94 for scope, both of which are relatively high compared to other Spanish negation annotated corpora. This corpus is publicly available under a Creative Commons Attribution Noncommercial-ShareAlike 4.0 International License ([[http://clic.ub.edu/corpus/es/node/171](http://clic.ub.edu/corpus/es/node/171)]([http://clic.ub.edu/corpus/es/node/171](http://clic.ub.edu/corpus/es/node/171)) (accessed on 13 November 2021)). Italian: [PERSON] et al. annotated two corpora from contrasting domains [28]. The first consists of 71 documents for stories adapted from Fact-Ita Bank [68]. The second consists of 301 tweets used in the Factuality Annotation (FactA) task at Evaluation of NLP and Speech Tools for Italian (EVALITA) 2016 [69]. The authors based their annotation guidelines on earlier guidelines [51; 55], including negation cues, scope, and focus. In general, every negation cue is associated with its scope and focus, and the first corpus of 1290 sentences contains 282 negating cues and 278 negated sentences. The second corpus comprises 59 negated sentences and 71 negation cues. The authors are to make the annotated data available on the Human Language Technology-Natural Language Processing (HLT-NLP) website at the FBK organization to implement a system for negation detection in Italian. The agreement on the annotation of the scope achieved roughly 0.7 and 0.6 for focus, where IAA was based on the average pairwise F-measure. English-Chinese: Many corpora in various natural languages have been annotated with monolingual negation to detect negation phenomena; however, they have not been studied in parallel across languages. The NegPar corpus is the first English-Chinese parallel corpus to be annotated with negation for narrative texts [15]. The corpus used four short stories from [PERSON]'s Sherlock Holmes short stories and mapped them to their Chinese translation by [PERSON]. The annotation guidelines of the ConanDoyle-neg corpus [41] were adapted for the English part of the corpus. Although the English side of the corpus had already been annotated, most was reannotated to capture semantic phenomena. [PERSON], a native Mandarin speaker, created the annotation guidelines for the Chinese part with support from the other two authors. Chinese translation often converts a positive English statement into a negative one; therefore, the number of negated sentences in the Chinese corpus is slightly higher than in the original English corpus. The annotation process was based on projections from the English corpus, where 1304 and 1762 negated sentences were annotated for the English and Chinese parts, respectively.