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  ### Dataset Summary
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- The CA-IT Parallel Corpus is a Catalan-Italian dataset of **XXX** parallel sentences. The dataset was created to support Catalan NLP tasks, e.g.,
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  Machine Translation.
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  ### Supported Tasks and Leaderboards
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  Two separated txt files are provided with the sentences sorted in the same order:
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- - xxx.ca: contains XXX Catalan sentences.
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- - xxx.it: contains XXX Italian sentences.
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  ### Data Splits
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  All corpora were collected from [Opus](https://opus.nlpl.eu/).
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- The remaining **XXX** sentences are synthetic parallel data created from a random sampling of the Spanish-Italian corpora available on [Opus](https://opus.nlpl.eu/) and translated into Catalan using the [PlanTL es-ca](https://huggingface.co/PlanTL-GOB-ES/mt-plantl-es-ca) model.
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  ### Data preparation
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  All datasets are deduplicated and filtered to remove any sentence pairs with a cosine similarity of less than 0.75.
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  This is done using sentence embeddings calculated using [LaBSE](https://huggingface.co/sentence-transformers/LaBSE).
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- The filtered datasets are then concatenated to form a final corpus of **XXX** parallel sentences and before training the punctuation is normalized using a modified version of the join-single-file.py script from [SoftCatalà](https://github.com/Softcatala/nmt-models/blob/master/data-processing-tools/join-single-file.py).
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  ### Personal and Sensitive Information
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  ### Dataset Summary
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+ The CA-IT Parallel Corpus is a Catalan-Italian dataset of **9.482.927** parallel sentences. The dataset was created to support Catalan NLP tasks, e.g.,
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  Machine Translation.
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  ### Supported Tasks and Leaderboards
 
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  Two separated txt files are provided with the sentences sorted in the same order:
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+ - ca-it_corpus.ca: contains 9.482.927 Catalan sentences.
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+ - ca-it_corpus.it: contains 9.482.927 Italian sentences.
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  ### Data Splits
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  All corpora were collected from [Opus](https://opus.nlpl.eu/).
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  ### Data preparation
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  All datasets are deduplicated and filtered to remove any sentence pairs with a cosine similarity of less than 0.75.
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  This is done using sentence embeddings calculated using [LaBSE](https://huggingface.co/sentence-transformers/LaBSE).
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+ The filtered datasets are then concatenated to form a final corpus of **9.482.927** parallel sentences and before training the punctuation is normalized using a modified version of the join-single-file.py script from [SoftCatalà](https://github.com/Softcatala/nmt-models/blob/master/data-processing-tools/join-single-file.py).
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  ### Personal and Sensitive Information
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