A Cascade Model for Proposition Extraction in Argumentation

Yohan Jo, Jacky Visser, Chris Reed, Eduard Hovy

Research output: Chapter in Book/Report/Conference proceedingConference contribution

9 Citations (Scopus)
229 Downloads (Pure)


We present a model to tackle a fundamental but understudied problem in computational argumentation: proposition extraction. Propositions are the basic units of an argument and the primary building blocks of most argument mining systems. However, they are usually substituted by argumentative discourse units obtained via surface-level text segmentation, which may yield text segments that lack semantic information necessary for subsequent argument mining processes. In contrast, our cascade model aims to extract complete propositions by handling anaphora resolution, text segmentation, reported speech, questions, imperatives, missing subjects, and revision. We formulate each task as a computational problem and test various models using a corpus of the 2016 U.S. presidential debates. We show promising performance for some tasks and discuss main challenges in proposition extraction.
Original languageEnglish
Title of host publicationProceedings of the 6th Workshop on Argument Mining
Place of PublicationFlorence, Italy
PublisherAssociation for Computational Linguistics
Number of pages14
Publication statusPublished - 1 Aug 2019


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