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MLQE-PE: A Multilingual Quality Estimation and Post-Editing Dataset

9 October 2020
M. Fomicheva
Shuo Sun
E. Fonseca
Chrysoula Zerva
Frédéric Blain
Vishrav Chaudhary
Francisco Guzmán
Nina Lopatina
Lucia Specia
André F. T. Martins
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Abstract

We present MLQE-PE, a new dataset for Machine Translation (MT) Quality Estimation (QE) and Automatic Post-Editing (APE). The dataset contains eleven language pairs, with human labels for up to 10,000 translations per language pair in the following formats: sentence-level direct assessments and post-editing effort, and word-level good/bad labels. It also contains the post-edited sentences, as well as titles of the articles where the sentences were extracted from, and the neural MT models used to translate the text.

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