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--- |
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license: cc-by-sa-4.0 |
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task_categories: |
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- summarization |
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language: |
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- fr |
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tags: |
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- NLP |
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- Debates |
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- Abstractive_Summarization |
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- Extractive_Summarization |
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- French |
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pretty_name: FREDsum |
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size_categories: |
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- n<1K |
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--- |
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# Dataset Summary |
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The FREDSum dataset is a comprehensive collection of transcripts and metadata from various political and public debates in France. The dataset aims to provide researchers, linguists, and data scientists with a rich source of debate content for analysis and natural language processing tasks. |
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## Languages |
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French |
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# Dataset Structure |
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The dataset is made of 144 debates, 115 of the debates make up the train set, while 29 make up the test set |
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## Data Fields |
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- id : Unique ID of an exemple |
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- Transcript : The text of the debate |
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- Abstractive_1-3 : Human summary of the debate. Abstractive summary style goes from least to most Abstractive - Abstractive 1 keeps names to avoid coreference resolution, while Abstractive 3 is free form |
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- Extractive_1-2 : Human selection of important utterances from the source debate |
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- Community 1-2 : Abstractive communities linking each of the abstractive sentences to the supporting extractive ones. Community 1 represents the linking between Abstractive 1 and Extractive 1, while Community 2 represents the linking between Abstractive 3 and Extractive 2 |
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## Data splits |
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- train : 115 |
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- test : 29 |
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# Licensing Information |
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non-commercial licence: CC BY-SA 4.0 |
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# Citation Information |
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If you use this dataset, please cite the following article: |
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Virgile Rennard, Guokan Shang, Damien Grari, Julie Hunter, and Michalis Vazirgiannis. 2023. FREDSum: A Dialogue Summarization Corpus for French Political Debates. In Findings of the Association for Computational Linguistics: EMNLP 2023, pages 4241–4253, Singapore. Association for Computational Linguistics. |
