mlsum-it 数据集卡片

数据集摘要

MLSum-it 数据集是 MLSum 的西班牙语部分翻译版本（Helsinki-NLP/opus-mt-es-it），包含从 BBC/mundo 获取的新闻文章。

更多信息请参考官方数据集页面 HuggingFace page 。

数据集包含两个特征：

• source：输入新闻文章。
• target：文章摘要。

支持的任务和排行榜

• abstractive-summarization，summarization

语言

该数据集中的文本为意大利语。

数据集结构

数据实例

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数据字段

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数据拆分

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数据集创建

策划理由

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源数据

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注释

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个人和敏感信息

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使用数据的注意事项

数据的社会影响

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数据偏见讨论

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其他已知限制

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其他信息

数据集策划者

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许可信息

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引用信息

更多详细信息和结果，请参考 published work

@Article{info13050228,
    AUTHOR = {Landro, Nicola and Gallo, Ignazio and La Grassa, Riccardo and Federici, Edoardo},
    TITLE = {Two New Datasets for Italian-Language Abstractive Text Summarization},
    JOURNAL = {Information},
    VOLUME = {13},
    YEAR = {2022},
    NUMBER = {5},
    ARTICLE-NUMBER = {228},
    URL = {https://www.mdpi.com/2078-2489/13/5/228},
    ISSN = {2078-2489},
    ABSTRACT = {Text summarization aims to produce a short summary containing relevant parts from a given text. Due to the lack of data for abstractive summarization on low-resource languages such as Italian, we propose two new original datasets collected from two Italian news websites with multi-sentence summaries and corresponding articles, and from a dataset obtained by machine translation of a Spanish summarization dataset. These two datasets are currently the only two available in Italian for this task. To evaluate the quality of these two datasets, we used them to train a T5-base model and an mBART model, obtaining good results with both. To better evaluate the results obtained, we also compared the same models trained on automatically translated datasets, and the resulting summaries in the same training language, with the automatically translated summaries, which demonstrated the superiority of the models obtained from the proposed datasets.},
    DOI = {10.3390/info13050228}
}