Pay Attention to Your Tone: Introducing a New Dataset for Polite Language Rewrite

• URL: http://arxiv.org/abs/2212.10190v1
• Date: Tue, 20 Dec 2022 12:02:34 GMT
• Title: Pay Attention to Your Tone: Introducing a New Dataset for Polite Language Rewrite
• Authors: Xun Wang, Tao Ge, Allen Mao, Yuki Li, Furu Wei, Si-Qing Chen
• Abstract summary: We introduce textscPoliteRewrite -- a dataset for polite language rewrite. TenK polite sentence rewrites annotated collaboratively by GPT-3.5 and human. 100K high-quality polite sentence rewrites by GPT-3.5 without human review.
• Score: 81.83910117028464
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: We introduce \textsc{PoliteRewrite} -- a dataset for polite language rewrite which is a novel sentence rewrite task. Compared with previous text style transfer tasks that can be mostly addressed by slight token- or phrase-level edits, polite language rewrite requires deep understanding and extensive sentence-level edits over an offensive and impolite sentence to deliver the same message euphemistically and politely, which is more challenging -- not only for NLP models but also for human annotators to rewrite with effort. To alleviate the human effort for efficient annotation, we first propose a novel annotation paradigm by a collaboration of human annotators and GPT-3.5 to annotate \textsc{PoliteRewrite}. The released dataset has 10K polite sentence rewrites annotated collaboratively by GPT-3.5 and human, which can be used as gold standard for training, validation and test; and 100K high-quality polite sentence rewrites by GPT-3.5 without human review. We wish this work (The dataset (10K+100K) will be released soon) could contribute to the research on more challenging sentence rewrite, and provoke more thought in future on resource annotation paradigm with the help of the large-scaled pretrained models.

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