Learning Sentence Ordering for Opinion Generation of Debate

Toshihiko Yanase, Toshinori Miyoshi, Kohsuke Yanai, Misa Sato, Makoto Iwayama, Yoshiki Niwa, Paul Reisert and Kentaro Inui

2nd Workshop on Argumentation Mining (ARG-MINING 2015)
Denver, Colorado, USA, June 4, 2015


We propose a sentence ordering method to help compose persuasive opinions for debating. In debate texts, support of an opinion such as evidence and reason typically follows the main claim. We focused on this claim-support structure to order sentences, and developed a two-step method. First, we select from among candidate sentences a first sentence that is likely to be a claim. Second, we order the remaining sentences by using a ranking-based method. We tested the effectiveness of the proposed method by comparing it with a general-purpose method of sentence ordering and found through experiment that it improves the accuracy of first sentence selection by about 19 percentage points and had a superior performance over all metrics. We also applied the proposed method to a constructive speech generation task.

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