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Idioms are an important language phenomenon in Chinese, but idiom translationis notoriously hard. Current machine translation models perform poorly on idiomtranslation, while idioms are sparse in many translation datasets. We presentPETCI, a parallel English translation dataset of Chinese idioms, aiming toimprove idiom translation by both human and machine. The dataset is built byleveraging human and machine effort. Baseline generation models showunsatisfactory abilities to improve translation, but structure-awareclassification models show good performance on distinguishing goodtranslations. Furthermore, the size of PETCI can be easily increased withoutexpertise. Overall, PETCI can be helpful to language learners and machinetranslation systems.

PETCI: A Parallel English Translation Dataset of Chinese Idioms