Datasets:
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README.md
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@@ -59,14 +59,7 @@ GeNTE (**Ge**nder-**N**eutral **T**ranslation **E**valuation) is a natural, bili
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Built from European Parliament speeches, GeNTE comprises a subset of the English-Italian portion of the [Europarl corpus](https://www.statmt.org/europarl/archives.html).
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GeNTE comprises 1500 parallel sentences, which are enriched with manual annotations and feature a balanced distribution of translation phenomena that either entail i) a gender-neutral translation (`Set-N`), or ii) a gendered translation in the target language (`Set-G`).
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* [_Hi Guys_ or _Hi Folks_? Benchmarking Gender-Neutral Machine Translation with the GeNTE Corpus](https://aclanthology.org/2023.emnlp-main.873/) (Piergentili et al., 2023 – EMNLP)
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* [A Prompt Response to the Demand for Automatic Gender-Neutral Translation](https://aclanthology.org/2024.eacl-short.23/) (Savoldi et al., 2024 – EACL)
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* [ItaEval and TweetyIta: A New Extensive Benchmark and Efficiency-First Language Model for Italian](https://ceur-ws.org/Vol-3878/6_main_long.pdf) (Attanasio et al., 2024 – CLiC-it)
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* [ItaEval: A CALAMITA Challenge](https://ceur-ws.org/Vol-3878/117_calamita_long.pdf) (Attanasio et al., 2024 – CALAMITA)
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* [GFG - Gender-Fair Generation: A CALAMITA Challenge](https://ceur-ws.org/Vol-3878/122_calamita_long.pdf) (Frenda et al., 2024 – CALAMITA)
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If you plan to use GeNTE in your work, please refer to the updated corpus available at [FBK-MT/mGeNTE](https://huggingface.co/datasets/FBK-MT/mGeNTE). This version should only be used for reproducibility purposes.
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### Supported Tasks and Languages
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To reproduce our results check out the code available at [fbk-NEUTR-evAL](https://github.com/hlt-mt/fbk-NEUTR-evAL/blob/main/solutions/GeNTE.md).
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## Dataset Structure
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Built from European Parliament speeches, GeNTE comprises a subset of the English-Italian portion of the [Europarl corpus](https://www.statmt.org/europarl/archives.html).
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GeNTE comprises 1500 parallel sentences, which are enriched with manual annotations and feature a balanced distribution of translation phenomena that either entail i) a gender-neutral translation (`Set-N`), or ii) a gendered translation in the target language (`Set-G`).
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If you plan to use GeNTE in your work, please refer to the updated corpus available at [FBK-MT/mGeNTE](https://huggingface.co/datasets/FBK-MT/mGeNTE).
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### Supported Tasks and Languages
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To reproduce our results check out the code available at [fbk-NEUTR-evAL](https://github.com/hlt-mt/fbk-NEUTR-evAL/blob/main/solutions/GeNTE.md).
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This version of GeNTE has been used in the following papers:
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* [_Hi Guys_ or _Hi Folks_? Benchmarking Gender-Neutral Machine Translation with the GeNTE Corpus](https://aclanthology.org/2023.emnlp-main.873/) (Piergentili et al., 2023 – EMNLP)
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* [A Prompt Response to the Demand for Automatic Gender-Neutral Translation](https://aclanthology.org/2024.eacl-short.23/) (Savoldi et al., 2024 – EACL)
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* [ItaEval and TweetyIta: A New Extensive Benchmark and Efficiency-First Language Model for Italian](https://ceur-ws.org/Vol-3878/6_main_long.pdf) (Attanasio et al., 2024 – CLiC-it)
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* [ItaEval: A CALAMITA Challenge](https://ceur-ws.org/Vol-3878/117_calamita_long.pdf) (Attanasio et al., 2024 – CALAMITA)
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* [GFG - Gender-Fair Generation: A CALAMITA Challenge](https://ceur-ws.org/Vol-3878/122_calamita_long.pdf) (Frenda et al., 2024 – CALAMITA)
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## Dataset Structure
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