FLUE is a French Language Understanding Evaluation benchmark. It consists of 5 tasks: Text Classification, Paraphrasing, Natural Language Inference, Constituency Parsing and Part-of-Speech Tagging, and Word Sense Disambiguation.
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MuMiN is a misinformation graph dataset containing rich social media data (tweets, replies, users, images, articles, hashtags), spanning 21 million tweets belonging to 26 thousand Twitter threads, each of which have been semantically linked to 13 thousand fact-checked claims across dozens of topics, events and domains, in 41 different languages, spanning more than a decade.
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FreSaDa is a French satire dataset for cross-domain satire detection, which is composed of 11,570 articles from the news domain. The dataset samples have been split into training, validation and test, such that the training publication sources are distinct from the validation and test publication sources. This gives rise to a cross-domain (cross-source) satire detection task.
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LLeQA is a French native dataset for studying information retrieval and long-form question answering in the legal domain. It consists of a knowledge corpus of 27,941 statutory articles collected from the Belgian legislation, and 1,868 legal questions posed by Belgian citizens and labeled by experienced jurists with a comprehensive answer rooted in relevant articles from the corpus.
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A corpus of 9k German and French user comments collected from migration-related news articles. It goes beyond the hate-neutral dichotomy and is instead annotated with 23 features, which in combination become descriptors of various types of speech, ranging from critical comments to implicit and explicit expressions of hate. The annotations are performed by 4 native speakers per language and achieve high (0.77) inter-annotator agreements.
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