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

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.
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.
MLQE-PE: A Multilingual Quality Estimation and Post-Editing Dataset
http://arxiv.org/abs/2010.04480v3