CovRelex: A COVID-19 Retrieval System with Relation Extraction

Vu Tran, Van-Hien Tran, Phuong Nguyen, Chau Nguyen, Ken Satoh, Yuji Matsumoto, Minh Nguyen


Abstract
This paper presents CovRelex, a scientific paper retrieval system targeting entities and relations via relation extraction on COVID-19 scientific papers. This work aims at building a system supporting users efficiently in acquiring knowledge across a huge number of COVID-19 scientific papers published rapidly. Our system can be accessed via https://www.jaist.ac.jp/is/labs/nguyen-lab/systems/covrelex/.
Anthology ID:
2021.eacl-demos.4
Volume:
Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations
Month:
April
Year:
2021
Address:
Online
Venue:
EACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
24–31
Language:
URL:
https://aclanthology.org/2021.eacl-demos.4
DOI:
10.18653/v1/2021.eacl-demos.4
Bibkey:
Cite (ACL):
Vu Tran, Van-Hien Tran, Phuong Nguyen, Chau Nguyen, Ken Satoh, Yuji Matsumoto, and Minh Nguyen. 2021. CovRelex: A COVID-19 Retrieval System with Relation Extraction. In Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations, pages 24–31, Online. Association for Computational Linguistics.
Cite (Informal):
CovRelex: A COVID-19 Retrieval System with Relation Extraction (Tran et al., EACL 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.eacl-demos.4.pdf
Data
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