A mention-based system for revision requirements detection

Ahmed Ruby, Christian Hardmeier, Sara Stymne

Research output: Conference Article in Proceeding or Book/Report chapterArticle in proceedingsResearchpeer-review

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 mentionlevel. 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.
Original languageEnglish
Title of host publicationProceedings of the First Workshop on Understanding Implicit and Underspecified Language (UnImplicit)
PublisherAssociation for Computational Linguistics
Publication date2021
Pages58-63
Publication statusPublished - 2021

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