Three Sentences Are All You Need: Local Path Enhanced Document Relation Extraction

06/03/2021
by   Quzhe Huang, et al.
0

Document-level Relation Extraction (RE) is a more challenging task than sentence RE as it often requires reasoning over multiple sentences. Yet, human annotators usually use a small number of sentences to identify the relationship between a given entity pair. In this paper, we present an embarrassingly simple but effective method to heuristically select evidence sentences for document-level RE, which can be easily combined with BiLSTM to achieve good performance on benchmark datasets, even better than fancy graph neural network based methods. We have released our code at https://github.com/AndrewZhe/Three-Sentences-Are-All-You-Need.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
09/29/2020

Double Graph Based Reasoning for Document-level Relation Extraction

Document-level relation extraction aims to extract relations among entit...
research
05/08/2022

GRAPHCACHE: Message Passing as Caching for Sentence-Level Relation Extraction

Entity types and textual context are essential properties for sentence-l...
research
10/22/2022

R^2F: A General Retrieval, Reading and Fusion Framework for Document-level Natural Language Inference

Document-level natural language inference (DOCNLI) is a new challenging ...
research
04/27/2022

Document-Level Relation Extraction with Sentences Importance Estimation and Focusing

Document-level relation extraction (DocRE) aims to determine the relatio...
research
11/11/2017

Commonsense LocatedNear Relation Extraction

LocatedNear relation describes two typically co-located objects, which i...
research
05/04/2022

Few-Shot Document-Level Relation Extraction

We present FREDo, a few-shot document-level relation extraction (FSDLRE)...
research
06/04/2021

Entity Concept-enhanced Few-shot Relation Extraction

Few-shot relation extraction (FSRE) is of great importance in long-tail ...

Please sign up or login with your details

Forgot password? Click here to reset