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task ID: negationdetection

Related Papers

Learning the Scope of Negation in Biomedical Texts

Authors: nan

Publication: TIPSTER (2008)

DOI: nan

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 …...

44848

FBK: Exploiting Phrasal and Contextual Clues for Negation Scope Detection

Authors: nan

Publication: TIPSTER (2012)

DOI: nan

Automatic detection of negation cues along with their scope and corresponding negated events is an important task that could bene- fit other natural language processing (NLP) tasks such as extraction …...

26288

Learning Structures of Negations from Flat Annotations

Authors: nan

Publication: TIPSTER (2015)

DOI: nan

We propose a novel method to learn negation expressions in a specialized (medical) domain. In our corpus, negations are annotated as ‘flat’ text spans. This allows for some infelicities in …...

26150

SWATAC: A Sentiment Analyzer using One-Vs-Rest Logistic Regression

Authors: nan

Publication: TIPSTER (2015)

DOI: nan

This paper describes SWATAC, a system built for SemEval-2015’s Task 10 Subtask B, namely the Message Polarity Classification Task. Given a tweet, the system classifies the sentiment as either positive, …...

22640

Automatic Negation and Speculation Detection in Veterinary Clinical Text

Authors: nan

Publication: TIPSTER (2017)

DOI: nan

The automatic detection of negation and speculation in clinical notes is vital when searching for genuine instances of a given phenomenon. This paper describes a new corpus of negation and …...

28535

Joint Entity Extraction and Assertion Detection for Clinical Text

Authors: nan

Publication: TIPSTER (2019)

DOI: nan

AbstractNegative medical findings are prevalent in clinical reports, yet discriminating them from positive findings remains a challenging task for in-formation extraction. Most of the existing systems treat this task as …...

39869

NegBERT: A Transfer Learning Approach for Negation Detection and Scope Resolution

Authors: nan

Publication: TIPSTER (2020)

DOI: nan

AbstractNegation is an important characteristic of language, and a major component of information extraction from text. This subtask is of considerable importance to the biomedical domain. Over the years, multiple …...

14138

IITK at SemEval-2021 Task 10: Source-Free Unsupervised Domain Adaptation using Class Prototypes

Authors: nan

Publication: TIPSTER (2021)

DOI: nan

AbstractRecent progress in deep learning has primarily been fueled by the availability of large amounts of annotated data that is obtained from highly expensive manual annotating pro-cesses. To tackle this …...

25699

SemEval-2021 Task 10: Source-Free Domain Adaptation for Semantic Processing

Authors: nan

Publication: TIPSTER (2021)

DOI: nan

AbstractThis paper presents the Source-Free Domain Adaptation shared task held within SemEval-2021. The aim of the task was to explore adaptation of machine-learning models in the face of data sharing …...

25708

The University of Arizona at SemEval-2021 Task 10: Applying Self-training, Active Learning and Data Augmentation to Source-free Domain Adaptation

Authors: nan

Publication: TIPSTER (2021)

DOI: nan

AbstractThis paper describes our systems for negation detection and time expression recognition in SemEval 2021 Task 10, Source-Free Domain Adaptation for Semantic Processing. We show that self-training, active learning and …...

25696

Improving negation detection with negation-focused pre-training

Authors: nan

Publication: TIPSTER (2022)

DOI: nan

AbstractNegation is a common linguistic feature that is crucial in many language understanding tasks, yet it remains a hard problem due to diversity in its expression in different types of …...

21099

Negation Detection in Dutch Spoken Human-Computer Conversations

Authors: nan

Publication: TIPSTER (2022)

DOI: nan

AbstractProper recognition and interpretation of negation signals in text or communication is crucial for any form of full natural language understanding. It is also essential for computational approaches to natural …...

16511