Chinese Sentence ParaphrasingDownload PDF

Anonymous

16 Feb 2024ACL ARR 2024 February Blind SubmissionReaders: Everyone
Abstract: Sentence paraphrasing involves understanding the semantics and generating alternative expressions that are equivalent to the original sentence but not identical. However, there lack of an evaluation metric for paraphrasing that aligns well with human annotation and a lack of high-quality Chinese paraphrase datasets which makes it difficult to train a Chinese paraphrase model. To address these challenges, we present the first large-scale automatically constructed Chinese sentence paraphrase corpus, consisting of 9.45 million annotated sentence pairs for paraphrasing. We also introduce a core dataset with 2.5 thousand Chinese sentence pairs that are completely paraphrased by the crowd and annotated by experts. With this high-quality data, we establish an automatic evaluation metric for Chinese paraphrasing evaluation, achieving a Spearman coefficient of 0.726 in human-annotated data and significantly outperforming existing metrics. Additionally, we build a strong baseline for Chinese paraphrasing generation with few entity and logical errors while preserving the meaning of the sentence and generating diverse and innovative sentences.
Paper Type: long
Research Area: NLP Applications
Contribution Types: NLP engineering experiment
Languages Studied: Chinese
Preprint Status: There is no non-anonymous preprint and we do not intend to release one.
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A1 Elaboration For Yes Or No: 8
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C1 Elaboration For Yes Or No: The model is open source and the training process only requires the most basic computing resources and a few hours.
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D4 Elaboration For Yes Or No: Not involving ethical review.
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E1 Elaboration For Yes Or No: 2
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