|
--- |
|
license: cc-by-4.0 |
|
task_categories: |
|
- translation |
|
language: |
|
- it |
|
- en |
|
--- |
|
|
|
This dataset adapts the [GeNTE dataset](https://huggingface.co/datasets/FBK-MT/GeNTE) to be run on [ItaEval](https://rita-nlp.org/sprints/itaeval/). |
|
In particular, we selected the five initial instances from the dataset and used them as few-shot examples ("train" split in this release). |
|
|
|
Please check the original dataset for more details on GeNTE. If you use the dataset, please consider citing the paper: |
|
|
|
```bibtex |
|
@inproceedings{piergentili-etal-2023-hi, |
|
title = "Hi Guys or Hi Folks? Benchmarking Gender-Neutral Machine Translation with the {G}e{NTE} Corpus", |
|
author = "Piergentili, Andrea and |
|
Savoldi, Beatrice and |
|
Fucci, Dennis and |
|
Negri, Matteo and |
|
Bentivogli, Luisa", |
|
editor = "Bouamor, Houda and |
|
Pino, Juan and |
|
Bali, Kalika", |
|
booktitle = "Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing", |
|
month = dec, |
|
year = "2023", |
|
address = "Singapore", |
|
publisher = "Association for Computational Linguistics", |
|
url = "https://aclanthology.org/2023.emnlp-main.873", |
|
doi = "10.18653/v1/2023.emnlp-main.873", |
|
pages = "14124--14140" |
|
} |
|
``` |
