---
license: unknown
language:
- de
- en
task_categories:
- text-classification
---

# QT21 De-En MQM Task from the PEER Benchmark (Performance Evaluation of Edit Representations)

Description from the [benchmark paper](https://arxiv.org/abs/2004.09143):
> A subset of 1,800 examples of the De-En QT21 dataset, annotated with details about the edits performed, namely the reason why each edit was applied. Since the dataset contains a large number of edit labels, we select the classes that are present in at least 100 examples and generate a modified version of the dataset for our purposes. Examples where no post-edit has been performed are also ignored.

The dataset was originally published at https://doi.org/10.5281/zenodo.4478266.

## Citations

PEER Benchmark:
```bibtex
@article{marrese-taylor-et-al-2021,
    title = {Variational Inference for Learning Representations of Natural Language Edits},
    volume = {35},
    url = {https://ojs.aaai.org/index.php/AAAI/article/view/17598}, DOI = {10.1609/aaai.v35i15.17598},
    number = {15},
    journal = {Proceedings of the AAAI Conference on Artificial Intelligence},
    author = {Marrese-Taylor, Edison and Reid, Machel and Matsuo, Yutaka},
    year = {2021},
    month = {May},
    pages = {13552-13560},
}
```

Original data source:
```bibtex
@inproceedings{burchardt-2013-multidimensional,
    title = "Multidimensional quality metrics: a flexible system for assessing translation quality",
    author = "Lommel, Arle Richard  and
      Burchardt, Aljoscha  and
      Uszkoreit, Hans",
    booktitle = "Proceedings of Translating and the Computer 35",
    month = nov # " 28-29",
    year = "2013",
    address = "London, UK",
    publisher = "Aslib",
    url = "https://aclanthology.org/2013.tc-1.6/"
}
```