Relation Extraction with Contextualized Relation Embedding (CRE)

Xiaoyu Chen, Rohan Badlani


Abstract
This submission is a paper that proposes an architecture for the relation extraction task which integrates semantic information with knowledge base modeling in a novel manner.
Anthology ID:
2020.deelio-1.2
Volume:
Proceedings of Deep Learning Inside Out (DeeLIO): The First Workshop on Knowledge Extraction and Integration for Deep Learning Architectures
Month:
November
Year:
2020
Address:
Online
Editors:
Eneko Agirre, Marianna Apidianaki, Ivan Vulić
Venue:
DeeLIO
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
11–19
Language:
URL:
https://aclanthology.org/2020.deelio-1.2
DOI:
10.18653/v1/2020.deelio-1.2
Bibkey:
Cite (ACL):
Xiaoyu Chen and Rohan Badlani. 2020. Relation Extraction with Contextualized Relation Embedding (CRE). In Proceedings of Deep Learning Inside Out (DeeLIO): The First Workshop on Knowledge Extraction and Integration for Deep Learning Architectures, pages 11–19, Online. Association for Computational Linguistics.
Cite (Informal):
Relation Extraction with Contextualized Relation Embedding (CRE) (Chen & Badlani, DeeLIO 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.deelio-1.2.pdf
Video:
 https://slideslive.com/38939725
Code
 codchen/CRE