---
license: cc-by-sa-4.0
language:
- fr
- en
size_categories:
- n<1K
---
# Dataset Card for DiscEvalMT


## Dataset Details

Contrastive test set for English-to-French MT evaluation covering 2 discourse phenomena: anaphora and lexical choice (coherence/cohesion).

### Dataset Description

For machine translation to tackle discourse phenomena, models must have access to extra-sentential linguistic context. There has been recent interest in modelling context in neural machine translation, but models have been principally evaluated with standard automatic metrics, poorly adapted to evaluating discourse phenomena. The aim of our article "Evaluating Discourse Phenomena in Neural Machine Translation" was to provide an alternative form of evaluation, specifically targeting discourse phenomena and the need for context beyond the level of the sentence.



- **Curated by:** Rachel Bawden, Rico Sennrich, Alexandra Birch, Alexandra and Barry Haddow
- **Language(s) (NLP):** English-to-French
- **License:** CC-BY-SA-4.0

### Dataset Sources [optional]

- **Repository:** [https://github.com/rbawden/discourse-mt-test-sets/tree/master](https://github.com/rbawden/discourse-mt-test-sets/tree/master)
- **Paper [optional]:** [Bawden et al., 2018. Evaluating Discourse Phenomena in Neural Machine Translation](https://www.aclweb.org/anthology/N18-1118)

## Uses

<!-- Address questions around how the dataset is intended to be used. -->

### Direct Use

<!-- This section describes suitable use cases for the dataset. -->

[More Information Needed]

### Out-of-Scope Use

<!-- This section addresses misuse, malicious use, and uses that the dataset will not work well for. -->

[More Information Needed]

## Dataset Structure

<!-- This section provides a description of the dataset fields, and additional information about the dataset structure such as criteria used to create the splits, relationships between data points, etc. -->

[More Information Needed]

## Dataset Creation

### Curation Rationale

<!-- Motivation for the creation of this dataset. -->

[More Information Needed]

### Source Data

Handcrafted examples (no specific domain) designed to be spontaneous, natural and varied.

#### Data Collection and Processing

Examples were manually created by the first author (native British English speaker, bilingual French) and checked by French native speakers.
Examples were inspired by similar examples found in subtitle data (in terms of syntactic structures, lexical choices, etc.) in order to encourage diversity and naturalness.


#### Personal and Sensitive Information

There is no personal or sensitive information in the dataset.

## Bias, Risks, and Limitations

<!-- This section is meant to convey both technical and sociotechnical limitations. -->

[More Information Needed]

### Recommendations

<!-- This section is meant to convey recommendations with respect to the bias, risk, and technical limitations. -->

Users should be made aware of the risks, biases and limitations of the dataset. More information needed for further recommendations.

## Citation [optional]

<!-- If there is a paper or blog post introducing the dataset, the APA and Bibtex information for that should go in this section. -->

**BibTeX:**

```\
@inproceedings{bawden-etal-2018-evaluating,
    title = "Evaluating Discourse Phenomena in Neural Machine Translation",
    author = "Bawden, Rachel and Sennrich, Rico and Birch, Alexandra and Haddow, Barry",
    booktitle = {{Proceedings of the 2018 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers)}},
    month = jun,
    year = "2018",
    address = "New Orleans, Louisiana",
    publisher = "Association for Computational Linguistics",
    url = "https://www.aclweb.org/anthology/N18-1118",
    doi = "10.18653/v1/N18-1118",
    pages = "1304--1313"
}
```

**APA:**

Bawden, R., Sennrich, R., Birch, A., & Haddow, B. (2018). Evaluating Discourse Phenomena in Neural Machine Translation. In Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 1 (Long Papers) (pp. 1304–1313). Association for Computational Linguistics.



## Dataset Card Authors

Rachel Bawden= rachel.bawden@inria.fr