Datasets:
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README.md
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- config_name: main
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data_files:
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- split: test
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path:
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- "en-es.tsv"
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default: true
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- config_name: common
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data_files:
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- split: test
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path:
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- "en-es_common.tsv"
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language:
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- en
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- it
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- es
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- de
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language_creators:
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- expert-generated
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license:
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The GeNTE corpus is released under a Creative Commons Attribution 4.0 International license (CC BY 4.0).
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## Contributions
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Thanks to [@BSavoldi](https://huggingface.co/BSavoldi) for adding this dataset.
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- config_name: main
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data_files:
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- split: test
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path: "GeNTE.tsv"
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default: true
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- config_name: common
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data_files:
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- split: test
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path: "GeNTE_common.tsv"
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language:
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- en
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- it
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language_creators:
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- expert-generated
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license:
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The GeNTE corpus is released under a Creative Commons Attribution 4.0 International license (CC BY 4.0).
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## Citation
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```bibtex
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@inproceedings{piergentili-etal-2023-hi,
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title = "Hi Guys or Hi Folks? Benchmarking Gender-Neutral Machine Translation with the {G}e{NTE} Corpus",
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author = "Piergentili, Andrea and
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Savoldi, Beatrice and
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Fucci, Dennis and
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Negri, Matteo and
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Bentivogli, Luisa",
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editor = "Bouamor, Houda and
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Pino, Juan and
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Bali, Kalika",
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booktitle = "Proceedings of the 2023 Conference on Empirical Methods in Natural Language Processing",
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month = dec,
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year = "2023",
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address = "Singapore",
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publisher = "Association for Computational Linguistics",
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url = "https://aclanthology.org/2023.emnlp-main.873",
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doi = "10.18653/v1/2023.emnlp-main.873",
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pages = "14124--14140"
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}
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```
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## Contributions
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Thanks to [@BSavoldi](https://huggingface.co/BSavoldi) for adding this dataset.
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