论文标题
MLQE-PE：多语言质量估计和后编辑数据集
MLQE-PE: A Multilingual Quality Estimation and Post-Editing Dataset
论文作者
论文摘要
我们提出了MLQE-PE，这是一种用于机器翻译（MT）质量估计（QE）和自动后编辑（APE）的新数据集。该数据集包含11个语言对，每个语言对的人体标签最多可用于以下格式：句子级直接评估和编辑后的工作，以及单词级的好/坏标签。它还包含后编辑的句子，以及从中提取句子的文章的标题，以及用于翻译文本的神经MT模型。
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.
