Abstract The CoNLL-2010 Shared Task was dedicated to the detection of uncertainty cues
and their linguistic scope in natural language texts. The motivation behind this task was that …

Traditionally, most research in NLP has focused on propositional aspects of meaning. To
truly understand language, however, extra-propositional aspects are equally important …

Uncertainty is an important linguistic phenomenon that is relevant in various Natural
Language Processing applications, in diverse genres from medical to community generated …

Speculation and negation are important information to identify text factuality. In this paper,
we propose a Convolutional Neural Network (CNN)-based model with probabilistic …

Neural networks with attention have proven effective for many natural language processing
tasks. In this paper, we develop attention mechanisms for uncertainty detection. In particular …

Uncertainty detection from text is essential in many applications in information retrieval (IR).
Detecting textual uncertainties helps extract factual information instead of uncertain or non …

This article explores a combination of deep and shallow approaches to the problem of
resolving the scope of speculation and negation within a sentence, specifically in the …

Background: Negation and speculation are critical elements in natural language processing
(NLP)-related tasks, such as information extraction, as these phenomena change the truth …

Motivation In recent years, there has been great progress in the field of automated curation
of biomedical networks and models, aided by text mining methods that provide evidence …

Hedges play an important role in the management of conversational interaction. In peer
tutoring, they are notably used by tutors in dyads (pairs of interlocutors) experiencing low …