PETCI: A Parallel English Translation Dataset of Chinese Idioms

Abstract

Idioms are an important language phenomenon in Chinese, but idiom translation is notoriously hard. Current machine translation models perform poorly on idiom translation, while idioms are sparse in many translation datasets. We present PETCI, a parallel English translation dataset of Chinese idioms, aiming to improve idiom translation by both human and machine. The dataset is built by leveraging human and machine effort. Baseline generation models show unsatisfactory abilities to improve translation, but structureaware classification models show good performance on distinguishing good translations. Furthermore, the size of PETCI can be easily increased without expertise. Overall, PETCI can be helpful to language learners and machine translation systems.

Generating Continuations in Multilingual Idiomatic Contexts

“…In the field of idiomaticity, prior works have focused on detecting idioms (Tayyar Madabushi et al, 2021;Tan and Jiang, 2021;, paraphrasing idiomatic sentences to literal paraphrases (Zhou et al, 2022), cloze task such as fill-in-the-blank language comprehension (Zheng et al, 2019), classifying idiomatic and literal expressions (Peng et al, 2015), translating idiomatic language (Tang, 2022), and generating continuations for idiomatic contexts (Chakrabarty et al, 2022).…”

Proceedings of the 3rd Workshop on Multi-lingual Representation Learning (MRL)

“…In the field of idiomaticity, prior works have focused on detecting idioms (Tayyar Madabushi et al, 2021;Tan and Jiang, 2021;, paraphrasing idiomatic sentences to literal paraphrases , cloze task such as fill-in-the-blank language comprehension (Zheng et al, 2019), classifying idiomatic and literal expressions (Peng et al, 2015), translating idiomatic language (Tang, 2022), and generating continuations for idiomatic contexts (Chakrabarty et al, 2022).…”