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This repository contains AMPERE++, the dataset associated with the paper “Efficient Argument Structure Extraction with Transfer Learning and Active Learning. Xinyu Hua and Lu Wang, Findings of ACL 2022”.
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It contains 400 academic peer reviews of ICLR 2018, collected from openreview.net in the prior work “Argument Mining for Understanding Peer Reviews”. Each review is already segmented into propositions on sub-sentence level. We further annotate support/attack relations among these propositions.
\n\nFor experiment purposes, we adopt the original train/val/test split. We provide the jsonl format with the following fields:
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