A Framework for Relation Extraction Across Multiple Datasets in Multiple Domains
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:
- 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)