Papers Negation Scope Resolution

Resolving Legalese: A Multilingual Exploration of Negation Scope Resolution in Legal Documents

Resolving the scope of a negation within a sentence is a challenging NLP task. The complexity of legal texts and the lack of annotated in-domain negation corpora pose challenges for state-of-the-art (SotA) models when pe…

No means ‘No’; a non-im-proper modeling approach, with embedded speculative context

Motivation: The medical data are complex in nature as terms that appear in records usually appear in different contexts. Through this paper, we investigate various bio model’s embeddings(BioBERT, BioE- LECTRA, PubMedBERT…

The Case of Imperfect Negation Cues: A Two-Step Approach for Automatic Negation Scope Resolution

Neural network-based methods are the state of the art in negation scope resolution. However, they often use the unrealistic assumption that cue information is completely accurate. Even if this assumption holds, the…

Scope resolution of predicted negation cues: A two-step neural network-based approach

Neural network-based methods are the state of the art in negation scope resolution. However, they often use the unrealistic assumption that cue information is completely accurate. Even if this assumption holds, there rem…

Negation typology and general representation models for cross-lingual zero-shot negation scope resolution in Russian, French, and Spanish.

Negation is a linguistic universal that poses difficulties for cognitive and computational processing. Despite many advances in text analytics, negation resolution remains an acute and continuously researched question in…

Negation Scope Resolution for Chinese as a Second Language

This paper studies Negation Scope Resolution (NSR) for Chinese as a Second Language (CSL), which shows many unique characteristics that distinguish itself from “standard” Chinese. We annotate a new moderate-sized corpus …

Multilingual Negation Scope Resolution for Clinical Text

Negation scope resolution is key to high-quality information extraction from clinical texts, but so far, efforts to make encoders used for information extraction negation-aware have been limited to English. We present a …

Orthogonal Attention: A Cloze-Style Approach to Negation Scope Resolution

Negation Scope Resolution is an extensively researched problem, which is used to locate the words affected by a negation cue in a sentence. Recent works have shown that simply finetuning transformer-based architectures y…

Multitask Learning of Negation and Speculation using Transformers

Detecting negation and speculation in language has been a task of considerable interest to the biomedical community, as it is a key component of Information Extraction systems from Biomedical documents. Prior work has in…

Resolving the Scope of Speculation and Negation using Transformer-Based Architectures

Speculation is a naturally occurring phenomena in textual data, forming an integral component of many systems, especially in the biomedical information retrieval domain. Previous work addressing cue detection and scope r…

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

Negation 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 approaches hav…

Simple Negation Scope Resolution through Deep Parsing: A Semantic Solution to a Semantic Problem