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... (read more)

PDF Abstract LREC 2020 PDF LREC 2020 Abstract

Datasets


  Add Datasets introduced or used in this paper

Results from the Paper


TASK DATASET MODEL METRIC NAME METRIC VALUE GLOBAL RANK USES EXTRA
TRAINING DATA
BENCHMARK
Negation Scope Resolution BioScope : Abstracts NegBERT F1 95.68 # 2
Negation Scope Resolution BioScope : Full Papers NegBERT F1 91.24 # 2
Negation Scope Resolution *sem 2012 Shared Task: Sherlock Dataset NegBERT F1 92.36 # 1
Negation Scope Resolution SFU Review Corpus NegBERT F1 90.95 # 2

Methods used in the Paper


METHOD TYPE
Weight Decay
Regularization
Residual Connection
Skip Connections
Adam
Stochastic Optimization
Layer Normalization
Normalization
Softmax
Output Functions
Scaled Dot-Product Attention
Attention Mechanisms
Dropout
Regularization
GELU
Activation Functions
Multi-Head Attention
Attention Modules
Attention Dropout
Regularization
WordPiece
Subword Segmentation
Linear Warmup With Linear Decay
Learning Rate Schedules
Dense Connections
Feedforward Networks
BERT
Language Models