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  ### Dataset Summary
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- The Catalan Government Crawling Corpus is a 39-million-token web corpus of Catalan built from the web. It has been obtained by crawling the .gencat domain and subdomains, belonging to the Catalan Government during September and October 2020. It consists of 39.117.909 tokens, 1.565.433 sentences and 71.043 documents. Documents are separated by single new lines. It is a subcorpus of the Catalan Textual Corpus.
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  ### Supported Tasks and Leaderboards
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  #### Initial Data Collection and Normalization
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  The corpus has been obtained by crawling the all the `.gencat.cat` domains during July 2020.
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- For preprocessing we used [Corpus-Cleaner](https://github.com/TeMU-BSC/corpus-cleaner-acl), a modular Python-based toolkit to clean raw text corpora through generator pipelines.
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  #### Who are the source language producers?
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  Ona de Gibert Bonet, Barcelona Supercomputing Center (ona.degibert@bsc.es)
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- This work was funded by the Departament de la Vicepresidència i de Polítiques Digitals i Territori de la Generalitat de Catalunya within the framework of the Aina project.
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  ### Licensing Information
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  ### Dataset Summary
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+ The Catalan Government Crawling Corpus is a 39-million-token web corpus of Catalan built from the web. It has been obtained by crawling the .gencat domain and subdomains, belonging to the Catalan Government during September and October 2020. It consists of 39,117,909 tokens, 1,565,433 sentences and 71,043 documents. Documents are separated by single new lines. It is a subcorpus of the Catalan Textual Corpus.
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  ### Supported Tasks and Leaderboards
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  #### Initial Data Collection and Normalization
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  The corpus has been obtained by crawling the all the `.gencat.cat` domains during July 2020.
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+ For preprocessing we used [Corpus-Cleaner](https://github.com/TeMU-BSC/corpus-cleaner-acl), a modular Python-based toolkit to clean raw text corpora through generator pipelines.
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  #### Who are the source language producers?
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  Ona de Gibert Bonet, Barcelona Supercomputing Center (ona.degibert@bsc.es)
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+ This work was funded by the Departament de la Vicepresidència i de Polítiques Digitals i Territori de la Generalitat de Catalunya within the framework of Projecte AINA.
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  ### Licensing Information
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