Idioms, are a kind of idiomatic expression in Chinese, most of which consist
of four Chinese characters. Due to the properties of non-compositionality and
metaphorical meaning, Chinese Idioms are hard to be understood by children and
non-native speakers. This study proposes a novel task, denoted as Chinese Idiom
Paraphrasing (CIP). CIP aims to rephrase idioms-included sentences to
non-idiomatic ones under the premise of preserving the original sentence's
meaning. Since the sentences without idioms are easier handled by Chinese NLP
systems, CIP can be used to pre-process Chinese datasets, thereby facilitating
and improving the performance of Chinese NLP tasks, e.g., machine translation
system, Chinese idiom cloze, and Chinese idiom embeddings. In this study, CIP
task is treated as a special paraphrase generation task. To circumvent
difficulties in acquiring annotations, we first establish a large-scale CIP
dataset based on human and machine collaboration, which consists of 115,530
sentence pairs. We further deploy three baselines and two novel CIP approaches
to deal with CIP problems. The results show that the proposed methods have
better performances than the baselines based on the established CIP dataset.

本文提出了中文成语改写（CIP）任务，以将包含成语的句子重新表述为不成语的句子并保留原本的意思，从而方便处理中文数据集和提高中文 NLP 任务的性能。本研究使用人与机器协作建立了一个包含 115,530 个句子对的大规模 CIP 数据集，并且使用三种基线模型和两种新方法，表现更好。