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---
annotations_creators:
- expert-generated
language:
- en
- fr
license: cc-by-sa-4.0
language_creators:
- expert-generated
multilinguality:
- translation
pretty_name: DiscEvalMT
size_categories:
- n<1K
source_datasets:
- original
tags:
- contextual-mt
- document-mt
- anaphora
- lexical-choice
- arxiv:2310.01188
task_categories:
- translation
task_ids: []
---
# Dataset Card for DiscEvalMT
## Table of Contents
- [Dataset Card for DiscEvalMT](#dataset-card-for-discevalmt)
- [Table of Contents](#table-of-contents)
- [Dataset Description](#dataset-description)
- [Dataset Summary](#dataset-summary)
- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
- [Machine Translation](#machine-translation)
- [Languages](#languages)
- [Dataset Structure](#dataset-structure)
- [Data Instances](#data-instances)
- [Dataset Creation](#dataset-creation)
- [Additional Preprocessing](#additional-preprocessing)
- [Additional Information](#additional-information)
- [Dataset Curators](#dataset-curators)
- [Licensing Information](#licensing-information)
- [Citation Information](#citation-information)
## Dataset Description
- **Repository:** [Github](https://github.com/rbawden/discourse-mt-test-sets)
- **Paper:** [NAACL 2018](https://www.aclweb.org/anthology/N18-1118)
- **Annotated Version:** [ICLR 2024](https://openreview.net/forum?id=XTHfNGI3zT)
- **Annotated Version:** [Arxiv](arxiv.org/abs/2310.01188)
- **Point of Contact:** [Rachel Bawden](mailto:[email protected])
### Dataset Summary
The DiscEvalMT dataset contains English-to-French translations used for resolving ambiguity in pronoun anaphora resolution and lexical choice (disambiguation and cohesion) context-aware translation. This version of the DiscEvalMT dataset contains further annotations of ambiguous spans and supporting context in the dataset examples to align it with the highlighting scheme of [SCAT](https://huggingface.co/inseq), enabling granular evaluations of context usage in context-aware NMT models.
**Disclaimer**: *The DiscEvalMT corpus was released in the NAACL 2018 paper ["Evaluating Discourse Phenomena in Neural Machine Translation"](https://www.aclweb.org/anthology/N18-1118) by Bawden et al. (2018), and an original version of the corpus is hosted on [Github](https://github.com/rbawden/discourse-mt-test-sets) with CC-BY-SA 4.0 license.*
### Supported Tasks and Leaderboards
#### Machine Translation
Refer to the [original paper](ttps://www.aclweb.org/anthology/N18-1118) for additional details on the evaluation of discourse-level phenomena using DiscEvalMT.
### Languages
The dataset contains handcrafted English-to-French translation examples containing either anaphoric pronouns or lexical choice items. Examples were created using existing [OpenSubtitles 2016](https://aclanthology.org/L16-1147/) sentences as reference for lexicon and syntactic structure.
## Dataset Structure
### Data Instances
The dataset contains two configurations (`anaphora` and `lexical-choice`), each containing only a test set of 200 examples each. Dataset examples have the following format:
```json
{
"id": 0,
"context_en": "The buildings will be finished next week.",
"en": "Soon they will be full of new residents.",
"context_fr": "Les bâtiments seront terminés la semaine prochaine.",
"fr": "Ils seront bientôt pleins de nouveaux résidents.",
"contrast_fr": "Elles seront bientôt pleines de nouveaux résidents.",
"context_en_with_tags": "The <hon>buildings<hoff> will be finished next week.",
"en_with_tags": "Soon <p>they</p> will be full of new residents.",
"context_fr_with_tags": "Les <hon>bâtiments<hoff> seront terminés la semaine prochaine.",
"fr_with_tags": "<p>Ils</p> seront bientôt pleins de nouveaux résidents.",
"contrast_fr_with_tags": "<p>Elles</p> seront bientôt pleines de nouveaux résidents.",
"type": "m.pl"
}
```
In every example, the context-dependent word of interest and its translation are surrounded by `<p>...</p>` tags. These are guaranteed to be found in the `en_with_tags`, `fr_with_tags` and `contrast_fr_with_tags` fields.
Any span surrounded by `<hon>...<hoff>` tags was identified by human annotators as supporting context necessary to correctly translate the pronoun of interest. These spans are found only in the `context_en_with_tags` and `context_fr_with_tags` fields.
In the example above, the translation of the pronoun `they` (field `en`) is ambiguous, and the correct translation to the feminine French pronoun `Ils` (in field `fr`) is only possible thanks to the supporting masculine noun `bâtiments` in the field `context_fr`.
Fields with the `_with_tags` suffix contain tags around pronouns of interest and supporting context, while their counterparts without the suffix contain the same text without tags, to facilitate direct usage with machine translation models.
### Dataset Creation
The dataset was created manually by the original authors, with context usage annotations added by the authors of [Quantifying the Plausibility of Context Reliance in Neural Machine Translation](tbd) for plausibility analysis purposes.
Please refer to the original article [Evaluating Discourse Phenomena in Neural Machine Translation](https://www.aclweb.org/anthology/N18-1118) for additional information on dataset creation.
### Additional Preprocessing
The dataset presents minor adjustments compared to the original DiscEvalMT corpus.
## Additional Information
### Dataset Curators
The original authors of DiscEvalMT are the curators of the original released dataset. For problems or updates on this 🤗 Datasets version, please contact [[email protected]](mailto:[email protected]).
### Licensing Information
The dataset is released under the original CC-BY-SA 4.0 license.
### Citation Information
Please cite the authors if you use these corpus in your work.
#### Original DiscEval-MT
```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"
}
```
#### Annotated version
```bibtex
@inproceedings{sarti-etal-2023-quantifying,
title = "Quantifying the Plausibility of Context Reliance in Neural Machine Translation",
author = "Sarti, Gabriele and
Chrupa{\l}a, Grzegorz and
Nissim, Malvina and
Bisazza, Arianna",
booktitle = "The Twelfth International Conference on Learning Representations (ICLR 2024)",
month = may,
year = "2024",
address = "Vienna, Austria",
publisher = "OpenReview",
url = "https://openreview.net/forum?id=XTHfNGI3zT"
}
``` |