AdaPrompt: Adaptive Prompt-based Finetuning for Relation Extraction

04/15/2021
by   Xiang Chen, et al.
0

In this paper, we reformulate the relation extraction task as mask language modeling and propose a novel adaptive prompt-based finetuning approach. We propose an adaptive label words selection mechanism that scatters the relation label into variable number of label tokens to handle the complex multiple label space. We further introduce an auxiliary entity discriminator object to encourage the model to focus on context representation learning. Extensive experiments on benchmark datasets demonstrate that our approach can achieve better performance on both the few-shot and supervised setting.

READ FULL TEXT
research
12/11/2018

RESIDE: Improving Distantly-Supervised Neural Relation Extraction using Side Information

Distantly-supervised Relation Extraction (RE) methods train an extractor...
research
01/10/2021

Adaptive Prototypical Networks with Label Words and Joint Representation Learning for Few-Shot Relation Classification

Relation classification (RC) task is one of fundamental tasks of informa...
research
03/30/2023

TLAG: An Informative Trigger and Label-Aware Knowledge Guided Model for Dialogue-based Relation Extraction

Dialogue-based Relation Extraction (DRE) aims to predict the relation ty...
research
10/25/2022

Better Few-Shot Relation Extraction with Label Prompt Dropout

Few-shot relation extraction aims to learn to identify the relation betw...
research
07/01/2017

Heterogeneous Supervision for Relation Extraction: A Representation Learning Approach

Relation extraction is a fundamental task in information extraction. Mos...
research
10/15/2022

A Novel Few-Shot Relation Extraction Pipeline Based on Adaptive Prototype Fusion

Few-shot relation extraction (FSRE) aims at recognizing unseen relations...
research
03/21/2021

Structural block driven - enhanced convolutional neural representation for relation extraction

In this paper, we propose a novel lightweight relation extraction approa...

Please sign up or login with your details

Forgot password? Click here to reset