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Updated description of the dataset format and content

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@@ -21,7 +21,7 @@ license: cc-by-nc-sa-4.0
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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 in NLP tasks, specifically
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  Machine Translation.
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  ### Supported Tasks and Leaderboards
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  ### Data Instances
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- Two separate txt files are provided with the sentences sorted in the same order:
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-
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- - ca-it_corpus.ca: contains 9.482.927 Catalan sentences.
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-
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- - ca-it_corpus.it: contains 9.482.927 Italian sentences.
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  ### Data Fields
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  #### Initial Data Collection and Normalization
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- The dataset is a combination of the following original datasets:
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-
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- | Dataset | Sentences |
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- |:--- | ---: |
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- | CCMatrix v1 | 7.757.357|
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- | MultiCCAligned v1 | 1.010.921|
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- | WikiMatrix | 271.587|
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- | GNOME | 1.198|
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- | KDE4 | 115.027 |
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- | OpenSubtitles | 225.732 |
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- | GlobalVoices| 5.209|
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-
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- All corpora were collected from [Opus](https://opus.nlpl.eu/).
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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.
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  #### Who are the source language producers?
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  ### Dataset Summary
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+ The CA-IT Parallel Corpus is a Catalan-Italian dataset parallel sentences created to support Catalan in NLP tasks, specifically
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  Machine Translation.
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  ### Supported Tasks and Leaderboards
 
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  ### Data Instances
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+ A single tsv file is provided with the sentences sorted in the same order and
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+ a header containing the two-letter ISO language code for the language in each column:
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+ ca-it_corpus.tsv.
 
 
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  ### Data Fields
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  #### Initial Data Collection and Normalization
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+ The dataset is a combination of the following original datasets collected from [Opus](https://opus.nlpl.eu/):
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+ CCMatrix, MultiCCAligned, WikiMatrix, GNOME, KDE4, OpenSubtitles, GlobalVoices.
 
 
 
 
 
 
 
 
 
 
 
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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 the final corpus.
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  #### Who are the source language producers?
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