paper
A Resource for Enthymeme Detection in Controversial Political Discourse
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a-resource-for-enthymeme-detection-in-controversial-political-discourse-ca838c2a·1 events·first seen 6d agoAliases: A Resource for Enthymeme Detection in Controversial Political Discourse
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Annotated dataset for enthymeme detection in political tweets with disagreement-aware training
Researchers present a dataset of 1,482 politically controversial tweets annotated by five annotators for enthymemes — arguments with unstated premises or conclusions — designed to study label variation rather than eliminate it. Annotation guidelines are grounded in Walton's argumentation schemes, and the paper includes a complexity analysis of cognitive load in the task. Preliminary experiments show that models trained on annotator disagreement outperform those trained on hard majority-vote labels, suggesting value in preserving annotation disagreement for subjective NLP tasks.