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---
license: cc-by-sa-4.0
task_categories:
- summarization
language:
- fr
tags:
- NLP
- Debates
- Abstractive_Summarization
- Extractive_Summarization
- French
pretty_name: FREDsum
size_categories:
- n<1K
---
# Dataset Summary
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.
## Languages
French
# Dataset Structure
The dataset is made of 144 debates, 115 of the debates make up the train set, while 29 make up the test set
## Data Fields
- id : Unique ID of an exemple
- Transcript : The text of the debate
- 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
- Extractive_1-2 : Human selection of important utterances from the source debate
- 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
## Data splits
- train : 115
- test : 29
# Licensing Information
non-commercial licence: CC BY-SA 4.0
# Citation Information
If you use this dataset, please cite the following article:
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. |