Hugging Face's logo

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 Viewer Files Community
3
apiergentili commited on
Commit
e54d1e7
·
verified ·
1 Parent(s): b09f6e6

addressed comments

Browse files
Files changed (1) hide show
  1. README.md +3 -2
README.md CHANGED
@@ -59,7 +59,6 @@ GeNTE (**Ge**nder-**N**eutral **T**ranslation **E**valuation) is a natural, bili
59
  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).
60
  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`).
61
 
62
- 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).
63
 
64
  ### Supported Tasks and Languages
65
 
@@ -71,7 +70,7 @@ To evaluate with GeNTE you can use the gender-neutrality classifier available on
71
 
72
  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/).
73
 
74
- 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).
75
 
76
  This version of GeNTE has been used in the following papers:
77
  * [_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:
80
  * [ItaEval: A CALAMITA Challenge](https://ceur-ws.org/Vol-3878/117_calamita_long.pdf) (Attanasio et al., 2024 – CALAMITA)
81
  * [GFG - Gender-Fair Generation: A CALAMITA Challenge](https://ceur-ws.org/Vol-3878/122_calamita_long.pdf) (Frenda et al., 2024 – CALAMITA)
82
 
 
 
83
  ## Dataset Structure
84
 
85
  ### Data Instances
 
59
  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).
60
  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`).
61
 
 
62
 
63
  ### Supported Tasks and Languages
64
 
 
70
 
71
  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/).
72
 
73
+ 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).
74
 
75
  This version of GeNTE has been used in the following papers:
76
  * [_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)
 
79
  * [ItaEval: A CALAMITA Challenge](https://ceur-ws.org/Vol-3878/117_calamita_long.pdf) (Attanasio et al., 2024 – CALAMITA)
80
  * [GFG - Gender-Fair Generation: A CALAMITA Challenge](https://ceur-ws.org/Vol-3878/122_calamita_long.pdf) (Frenda et al., 2024 – CALAMITA)
81
 
82
+ 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).
83
+
84
  ## Dataset Structure
85
 
86
  ### Data Instances