ILPost 的数据集卡片

数据集概述

ILPost 数据集，包含从 ILPost 获取的新闻文章。

有两个特征：

• source: 新闻文章的输入。
• target: 文章的摘要。

支持的任务和排行榜

• abstractive-summarization(提炼摘要) ，summarization(摘要)

语言

数据集中的文本是用意大利语编写的

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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使用数据的考虑事项

数据集的社会影响

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偏见讨论

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其他已知限制

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附加信息

数据集策划者

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授权信息

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引用信息

在 published work 中提供更多详细信息和结果

@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}
}