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maximoss/rte3-french

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Permissive or share-alike

The declared licence (cc-by-4.0) is classified as permissive.

Declared licence: cc-by-4.0, from the tagEvidence: README.md at 435d7a2
Licence files: No licence file at the top level of the repositoryEvidence: file list at 435d7a2
Declared sources: None listed in the card metadata
Access gated on Hugging Face: No

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Tasks

text-classification

Citation text from the card

@inproceedings{skandalis-etal-2024-new-datasets,
    title = "New Datasets for Automatic Detection of Textual Entailment and of Contradictions between Sentences in {F}rench",
    author = "Skandalis, Maximos  and
      Moot, Richard  and
      Retor{\'e}, Christian  and
      Robillard, Simon",
    editor = "Calzolari, Nicoletta  and
      Kan, Min-Yen  and
      Hoste, Veronique  and
      Lenci, Alessandro  and
      Sakti, Sakriani  and
      Xue, Nianwen",
    booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)",
    month = may,
    year = "2024",
    address = "Torino, Italy",
    publisher = "ELRA and ICCL",
    url = "https://aclanthology.org/2024.lrec-main.1065",
    pages = "12173--12186",
    abstract = "This paper introduces DACCORD, an original dataset in French for automatic detection of contradictions between sentences. It also presents new, manually translated versions of two datasets, namely the well known dataset RTE3 and the recent dataset GQNLI, from English to French, for the task of natural language inference / recognising textual entailment, which is a sentence-pair classification task. These datasets help increase the admittedly limited number of datasets in French available for these tasks. DACCORD consists of 1034 pairs of sentences and is the first dataset exclusively dedicated to this task and covering among others the topic of the Russian invasion in

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dataset_licence({ "id": "maximoss/rte3-french" })
signal: "permissive"
stated_licence: "cc-by-4.0"
sources: 0