--- 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:rachel.bawden@inria.fr) ### 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 buildings will be finished next week.", "en_with_tags": "Soon

they

will be full of new residents.", "context_fr_with_tags": "Les bâtiments seront terminés la semaine prochaine.", "fr_with_tags": "

Ils

seront bientôt pleins de nouveaux résidents.", "contrast_fr_with_tags": "

Elles

seront bientôt pleines de nouveaux résidents.", "type": "m.pl" } ``` In every example, the context-dependent word of interest and its translation are surrounded by `

...

` 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 `...` 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 [gabriele.sarti996@gmail.com](mailto:gabriele.sarti996@gmail.com). ### 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" } ```