A Framework for Relation Extraction Across Multiple Datasets in Multiple Domains

Geeticka Chauhan, Matthew McDermott, Peter Szolovits


Abstract
In this work, we aim to build a unifying framework for relation extraction (RE), applying this on 3 highly used datasets with the ability to be extendable to new datasets. At the moment, the domain suffers from lack of reproducibility as well as a lack of consensus on generalizable techniques. Our framework will be open-sourced and will aid in performing systematic exploration on the effect of different modeling techniques, pre-processing, training methodologies and evaluation metrics on the 3 datasets to help establish a consensus.
Anthology ID:
W19-3608
Volume:
Proceedings of the 2019 Workshop on Widening NLP
Month:
August
Year:
2019
Address:
Florence, Italy
Editors:
Amittai Axelrod, Diyi Yang, Rossana Cunha, Samira Shaikh, Zeerak Waseem
Venue:
WiNLP
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
18–20
Language:
URL:
https://aclanthology.org/W19-3608
DOI:
Bibkey:
Cite (ACL):
Geeticka Chauhan, Matthew McDermott, and Peter Szolovits. 2019. A Framework for Relation Extraction Across Multiple Datasets in Multiple Domains. In Proceedings of the 2019 Workshop on Widening NLP, pages 18–20, Florence, Italy. Association for Computational Linguistics.
Cite (Informal):
A Framework for Relation Extraction Across Multiple Datasets in Multiple Domains (Chauhan et al., WiNLP 2019)
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