Datasets:

maximoss
/

sick-fr

@@ -25,14 +25,12 @@ size_categories:
 ### Dataset Summary
-This repository contains a machine-translated French version of [SICK](https://huggingface.co/datasets/sick) (Sentences Involving Compositional Knowldedge) dataset, with some manual corrections over the translations produced. The goal is to predict textual entailment (does sentence A
 imply/contradict/neither sentence B), which is a classification task (given two sentences, predict one of three labels). Apart from translating the sentence pairs, the rest of information (pair ID, labels, source dataset of each sentence, train/dev/test subset partition) has been left intact as in the original English dataset.
 For every sentence pair translated to French, the repository also contains the original sentences in English, so that it can also be used for multilingual or crosslingual tasks.
 The dataset is here formatted in a similar manner (TSV format) as the widely used [XNLI](https://huggingface.co/datasets/xnli) dataset for convenience.
-The machine translation produced in the present repository should be of pretty decent quality, given the average short length of the sentences in SICK dataset. Some of the translations were also manually corrected.
 ### Supported Tasks and Leaderboards
 This dataset can be used for the task of Natural Language Inference (NLI), also known as Recognizing Textual Entailment (RTE), which is a sentence-pair classification task.
@@ -78,7 +76,7 @@ For the B-A order:
 The dataset was machine translated from English to French using the latest neural machine translation [opus-mt-tc-big](https://huggingface.co/Helsinki-NLP/opus-mt-tc-big-en-fr) model available for French.
 The translation of the sentences was carried out on November 26th, 2023.
-Some of the translations were manually corrected.
 ## Additional Information

 ### Dataset Summary
+This repository contains a machine-translated, manually corrected French version of [SICK](https://huggingface.co/datasets/sick) (Sentences Involving Compositional Knowldedge) dataset, with some manual corrections over the translations produced. The goal is to predict textual entailment (does sentence A
 imply/contradict/neither sentence B), which is a classification task (given two sentences, predict one of three labels). Apart from translating the sentence pairs, the rest of information (pair ID, labels, source dataset of each sentence, train/dev/test subset partition) has been left intact as in the original English dataset.
 For every sentence pair translated to French, the repository also contains the original sentences in English, so that it can also be used for multilingual or crosslingual tasks.
 The dataset is here formatted in a similar manner (TSV format) as the widely used [XNLI](https://huggingface.co/datasets/xnli) dataset for convenience.
 ### Supported Tasks and Leaderboards
 This dataset can be used for the task of Natural Language Inference (NLI), also known as Recognizing Textual Entailment (RTE), which is a sentence-pair classification task.
 The dataset was machine translated from English to French using the latest neural machine translation [opus-mt-tc-big](https://huggingface.co/Helsinki-NLP/opus-mt-tc-big-en-fr) model available for French.
 The translation of the sentences was carried out on November 26th, 2023.
+The translated sentences were then manually corrected in 2025.
 ## Additional Information