A Mention-Based System for Revision Requirements Detection

Ahmed Ruby, Christian Hardmeier, Sara Stymne


Abstract
Exploring aspects of sentential meaning that are implicit or underspecified in context is important for sentence understanding. In this paper, we propose a novel architecture based on mentions for revision requirements detection. The goal is to improve understandability, addressing some types of revisions, especially for the Replaced Pronoun type. We show that our mention-based system can predict replaced pronouns well on the mention-level. However, our combined sentence-level system does not improve on the sentence-level BERT baseline. We also present additional contrastive systems, and show results for each type of edit.
Anthology ID:
2021.unimplicit-1.7
Volume:
Proceedings of the 1st Workshop on Understanding Implicit and Underspecified Language
Month:
August
Year:
2021
Address:
Online
Venue:
unimplicit
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
58–63
Language:
URL:
https://aclanthology.org/2021.unimplicit-1.7
DOI:
10.18653/v1/2021.unimplicit-1.7
Bibkey:
Cite (ACL):
Ahmed Ruby, Christian Hardmeier, and Sara Stymne. 2021. A Mention-Based System for Revision Requirements Detection. In Proceedings of the 1st Workshop on Understanding Implicit and Underspecified Language, pages 58–63, Online. Association for Computational Linguistics.
Cite (Informal):
A Mention-Based System for Revision Requirements Detection (Ruby et al., unimplicit 2021)
Copy Citation:
PDF:
https://aclanthology.org/2021.unimplicit-1.7.pdf