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Datasets:
FBK-MT
/
GeNTE

Tasks:
Translation
Text Generation
Modalities:
Text
Formats:
csv
Sub-tasks:
language-modeling
Languages:
English
Italian
Size:
1K - 10K
Tags:
gender
bias
inclusivity
rewriting
translation
mt
Libraries:
Datasets
pandas
License:
Dataset card Data Studio Files
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README.md CHANGED
@@ -59,7 +59,6 @@ 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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- 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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@@ -71,7 +70,7 @@ To evaluate with GeNTE you can use the gender-neutrality classifier available on
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  For additional details on evaluation with GeNTE, please refer to the paper [*Hi Guys* or *Hi Folks?* Benchmarking Gender-Neutral Machine Translation with the GeNTE Corpus](https://aclanthology.org/2023.emnlp-main.873/).
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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)
@@ -80,6 +79,8 @@ This version of GeNTE has been used in the following papers:
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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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  ### Data Instances
 
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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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  ### Supported Tasks and Languages
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  For additional details on evaluation with GeNTE, please refer to the paper [*Hi Guys* or *Hi Folks?* Benchmarking Gender-Neutral Machine Translation with the GeNTE Corpus](https://aclanthology.org/2023.emnlp-main.873/).
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+ Code and data for the classifier are 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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  * [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).
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+
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  ## Dataset Structure
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  ### Data Instances