We use the NLP toolchain that is used to construct the Groningen Meaning Bank to address the task of detecting negation cue and scope, as defined in the shared task “Resolving the Scope and Focus of Negation”. This toolchain applies the C&C tools for parsing, using the formalism of Combinatory Categorial Grammar, and applies Boxer to produce semantic representations in the form of Discourse Rep...

Negation detection is a key component in clinical information extraction systems, as health record text contains reasonings in which the physician excludes different diagnoses by negating them. Many systems for negation detection rely on negation cues (e.g. not), but only few studies have investigated if the syntactic structure of the sentences can be used for determining the scope of these cue...

Automatic detection of negation cues along with their scope and corresponding negated events is an important task that could benefit other natural language processing (NLP) tasks such as extraction of factual information from text, sentiment analysis, etc. This paper presents a system for this task that exploits phrasal and contextual clues apart from various token specific features. The system...

The automatically processing of texts has become a very important aim in the recent years because of the huge amount of time that could be saved in sectors such as education, jurisprudence or medicine. Thus, a very important task in the automatically processing of texts is the detection of language mechanism, such as modality and negation. In this paper we present our first approach in the fiel...

Automatic negation scope detection is a task that has been tackled using different classifiers and heuristics. Most systems are however 1) highly-engineered, 2) English-specific, and 3) only tested on the same genre they were trained on. We start by addressing 1) and 2) using a neural network architecture. Results obtained on data from the *SEM2012 shared task on negation scope detection show t...

BACKGROUND The treatment of negation and hedging in natural language processing has received much interest recently, especially in the biomedical domain. However, open access corpora annotated for negation and/or speculation are hardly available for training and testing applications, and even if they are, they sometimes follow different design principles. In this paper, the annotation principle...

In this paper we describe the creation of a consensus corpus that was obtained through combining three individual annotations of the same clinical corpus in Swedish. We used a few basic rules that were executed automatically to create the consensus. The corpus contains negation words, speculative words, uncertain expressions and certain expressions. We evaluated the consensus using it for negat...

In this paper we present a machine learning system that finds the scope of negation in biomedical texts. The system consists of two memory-based engines, one that decides if the tokens in a sentence are negation signals, and another that finds the full scope of these negation signals. Our approach to negation detection differs in two main aspects from existing research on negation. First, we fo...

This paper proposes an annotation scheme for the focus of negation in Japanese text. Negation has its scope and the focus within the scope. The scope of negation is the part of the sentence that is negated; the focus is the part of the scope that is most prominently or explicitly negated. In natural language processing, correct interpretation of negated statements requires precise detection of ...