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Improve reference to mGeNTE (#3)

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- Improve reference to mGeNTE (51c160992b8af8e627f6cb02513cdb3f2ba53208)
- addressed comments (b09f6e64ee9f49aa04e8f0d4824f05ace6ee89d8)
- addressed comments (e54d1e7c1a2cbd1265158e5243a7c384729a69be)


Co-authored-by: Andrea Piergentili <[email protected]>

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  1. README.md +17 -8
README.md CHANGED
@@ -44,7 +44,7 @@ task_ids:
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- # 🚨 Check out [**mGeNTE**](https://huggingface.co/datasets/FBK-MT/mGeNTE), new multilingual release of the corpus.
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  -------------------------------------------------------------------------------------------------------------------
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  # Dataset Card for GeNTE
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  **Homepage:** https://mt.fbk.eu/gente/
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- ### Dataset Summary
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  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.
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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
@@ -67,19 +66,29 @@ GeNTE comprises 1500 parallel sentences, which are enriched with manual annotati
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  GeNTE supports cross-lingual (en-it) and intra-lingual (it-it) gender inclusive translation tasks.
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- 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/) for additional details on evaluation with GeNTE.
 
 
 
 
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- The evaluation code is 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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  ### Data Instances
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- The dataset consists of two configuration types (`main` and `common`) corrisponding to the files:
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  - **`GeNTE.tsv`:** The complete GeNTE corpus and its set annotations
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- - **`GeNTE_common.tsv`:** Subset of the GeNTE corpus that comprises 3 alternative gender-neutral reference translations
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  ### Data Fields
 
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+ # 🚨 GeNTE has been superseded by [**mGeNTE**](https://huggingface.co/datasets/FBK-MT/mGeNTE), a new multilingual release of the corpus with additional annotations.
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  -------------------------------------------------------------------------------------------------------------------
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  # Dataset Card for GeNTE
 
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  **Homepage:** https://mt.fbk.eu/gente/
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+ ## Dataset Summary
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  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.
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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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  GeNTE supports cross-lingual (en-it) and intra-lingual (it-it) gender inclusive translation tasks.
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+ 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).
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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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+ * [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).
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  ## Dataset Structure
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  ### Data Instances
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+ The dataset consists of two configuration types (`main` and `common`) corresponding to the files:
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  - **`GeNTE.tsv`:** The complete GeNTE corpus and its set annotations
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+ - **`GeNTE_common.tsv`:** Subset of the GeNTE corpus that comprises 3 alternative gender-neutral reference translations
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  ### Data Fields