Datasets:
Improve reference to mGeNTE (#3)
Browse files- Improve reference to mGeNTE (51c160992b8af8e627f6cb02513cdb3f2ba53208)
- addressed comments (b09f6e64ee9f49aa04e8f0d4824f05ace6ee89d8)
- addressed comments (e54d1e7c1a2cbd1265158e5243a7c384729a69be)
Co-authored-by: Andrea Piergentili <[email protected]>
README.md
CHANGED
@@ -44,7 +44,7 @@ task_ids:
|
|
44 |
---
|
45 |
|
46 |
-------------------------------------------------------------------------------------------------------------------
|
47 |
-
# 🚨
|
48 |
-------------------------------------------------------------------------------------------------------------------
|
49 |
|
50 |
# Dataset Card for GeNTE
|
@@ -52,13 +52,12 @@ task_ids:
|
|
52 |
**Homepage:** https://mt.fbk.eu/gente/
|
53 |
|
54 |
|
55 |
-
|
56 |
|
57 |
GeNTE (**Ge**nder-**N**eutral **T**ranslation **E**valuation) is a natural, bilingual corpus designed to benchmark the ability of machine translation systems to generate gender-neutral translations.
|
58 |
|
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 (`
|
61 |
-
|
62 |
|
63 |
|
64 |
### Supported Tasks and Languages
|
@@ -67,19 +66,29 @@ GeNTE comprises 1500 parallel sentences, which are enriched with manual annotati
|
|
67 |
|
68 |
GeNTE supports cross-lingual (en-it) and intra-lingual (it-it) gender inclusive translation tasks.
|
69 |
|
70 |
-
|
|
|
|
|
|
|
|
|
71 |
|
72 |
-
|
|
|
|
|
|
|
|
|
|
|
73 |
|
|
|
74 |
|
75 |
## Dataset Structure
|
76 |
|
77 |
### Data Instances
|
78 |
|
79 |
-
The dataset consists of two configuration types (`main` and `common`)
|
80 |
|
81 |
- **`GeNTE.tsv`:** The complete GeNTE corpus and its set annotations
|
82 |
-
-
|
83 |
|
84 |
|
85 |
### Data Fields
|
|
|
44 |
---
|
45 |
|
46 |
-------------------------------------------------------------------------------------------------------------------
|
47 |
+
# 🚨 GeNTE has been superseded by [**mGeNTE**](https://huggingface.co/datasets/FBK-MT/mGeNTE), a new multilingual release of the corpus with additional annotations.
|
48 |
-------------------------------------------------------------------------------------------------------------------
|
49 |
|
50 |
# Dataset Card for GeNTE
|
|
|
52 |
**Homepage:** https://mt.fbk.eu/gente/
|
53 |
|
54 |
|
55 |
+
## Dataset Summary
|
56 |
|
57 |
GeNTE (**Ge**nder-**N**eutral **T**ranslation **E**valuation) is a natural, bilingual corpus designed to benchmark the ability of machine translation systems to generate gender-neutral translations.
|
58 |
|
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
|
|
|
66 |
|
67 |
GeNTE supports cross-lingual (en-it) and intra-lingual (it-it) gender inclusive translation tasks.
|
68 |
|
69 |
+
To evaluate with GeNTE you can use the gender-neutrality classifier available on Hugging Face at [FBK-MT/GeNTE-evaluator](https://huggingface.co/FBK-MT/GeNTE-evaluator).
|
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)
|
77 |
+
* [A Prompt Response to the Demand for Automatic Gender-Neutral Translation](https://aclanthology.org/2024.eacl-short.23/) (Savoldi et al., 2024 – EACL)
|
78 |
+
* [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)
|
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
|
87 |
|
88 |
+
The dataset consists of two configuration types (`main` and `common`) corresponding to the files:
|
89 |
|
90 |
- **`GeNTE.tsv`:** The complete GeNTE corpus and its set annotations
|
91 |
+
- **`GeNTE_common.tsv`:** Subset of the GeNTE corpus that comprises 3 alternative gender-neutral reference translations
|
92 |
|
93 |
|
94 |
### Data Fields
|