Several corpora have been annotated with negation scope—the set of words whose meaning is negated by a cue like the word “not”—leading to the development of classifiers that detect negation scope with high accuracy. We show that for nearly all of these corpora, this high accuracy can be attributed to a single fact: they frequently annotate negation scope as a single span of text delimited by pu...

A review of published work in clinical natural language processing (NLP) may suggest that the negation detection task has been "solved." This work proposes that an optimizable solution does not equal a generalizable solution. We introduce a new machine learning-based Polarity Module for detecting negation in clinical text, and extensively compare its performance across domains. Using four manua...

Extracting biomedical relations from text is an important task in BioMedical NLP. There are several systems developed for this purpose but the ones on Drug-Drug interactions are still a few. In this paper we want to show the effectiveness of negation features for this task. We firstly describe how we extended the DrugDDI corpus by annotating it with the scope of negation, and secondly we report...

Negation is an important linguistic phenomenon that needs to be considered for identifying correct sentiments from the opinionated data available in digital form. It has power alter polarity or strength of affected words. In this paper, authors present a survey on negation role been done until now sentiment analysis, specifically Twitter analysis. The discuss various approaches modelling partic...

This paper presents an approach that exploits the scope of negation cues for relation extraction (RE) without the need of using any specifically annotated dataset for building a separate negation scope detection classifier. New features are proposed which are used in two different stages. These also include non-target entity specific features. The proposed RE approach outperforms the previous s...

Simply detecting negation cues is not sufficient to determine the semantics of negation, scope and focus must be taken into account. While scope detection has recently seen repeated attention, the linguistic notion of focus is only now being introduced into computational work. The *Sem2012 Shared Task is pioneering this effort by introducing a suitable dataset and annotation guidelines. CLaC’s ...

paper proposes a linguistically motivated approach to deal with negation in the context of information extraction. This approach is used in a practical application: the automatic detection of cases of hospital acquired infections (HAI) by processing unstructured medical discharge summaries. One of the important processing steps is the extraction of specific terms expressing risk indicators that...

NLP techniques have been widely adopted in the biomedical domain to perform various text-analytics tasks, such as searching literature and extracting deriving new knowledge from data. One type of data is clinical texts (e.g., cases medical records), which typically contain physicians’ notes about a patient’s health, including previous history (symptoms, diseases, lab exams, treatm...