Deep Neural Approaches to Relation Triplets Extraction: A Comprehensive Survey

by   Tapas Nayak, et al.

Recently, with the advances made in continuous representation of words (word embeddings) and deep neural architectures, many research works are published in the area of relation extraction and it is very difficult to keep track of so many papers. To help future research, we present a comprehensive review of the recently published research works in relation extraction. We mostly focus on relation extraction using deep neural networks which have achieved state-of-the-art performance on publicly available datasets. In this survey, we cover sentence-level relation extraction to document-level relation extraction, pipeline-based approaches to joint extraction approaches, annotated datasets to distantly supervised datasets along with few very recent research directions such as zero-shot or few-shot relation extraction, noise mitigation in distantly supervised datasets. Regarding neural architectures, we cover convolutional models, recurrent network models, attention network models, and graph convolutional models in this survey.


Neural relation extraction: a survey

Neural relation extraction discovers semantic relations between entities...

Zero-shot Temporal Relation Extraction with ChatGPT

The goal of temporal relation extraction is to infer the temporal relati...

Few-Shot Document-Level Relation Extraction

We present FREDo, a few-shot document-level relation extraction (FSDLRE)...

Deep Neural Network Based Relation Extraction: An Overview

Knowledge is a formal way of understanding the world, providing a human-...

Deep Residual Learning for Weakly-Supervised Relation Extraction

Deep residual learning (ResNet) is a new method for training very deep n...

Relation Extraction : A Survey

With the advent of the Internet, large amount of digital text is generat...

Supervised Neural Models Revitalize the Open Relation Extraction

Open relation extraction (ORE) remains a challenge to obtain a semantic ...

Please sign up or login with your details

Forgot password? Click here to reset