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README.md
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---
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language:
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- ca
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- it
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- multilingual
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multilinguality:
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- translation
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pretty_name: CA-IT Parallel Corpus
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size_categories:
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- 1M<n<10M
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source_datasets:
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- original
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task_categories:
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- translation
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task_ids: []
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---
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# Dataset Card for CA-IT Parallel Corpus
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## Table of Contents
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- [Dataset Description](#dataset-description)
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- [Dataset Summary](#dataset-summary)
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- [Supported Tasks](#supported-tasks-and-leaderboards)
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- [Languages](#languages)
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- [Dataset Structure](#dataset-structure)
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- [Data Splits](#data-instances)
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- [Dataset Creation](#dataset-creation)
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- [Source Data](#source-data)
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- [Data preparation](#data-preparation)
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- [Personal and Sensitive Information](#personal-and-sensitive-information)
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- [Considerations for Using the Data](#considerations-for-using-the-data)
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- [Social Impact of Dataset](#social-impact-of-dataset)
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- [Discussion of Biases](#discussion-of-biases)
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- [Other Known Limitations](#other-known-limitations)
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- [Additional Information](#additional-information)
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- [Author](#author)
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- [Contact Information](#contact-information)
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- [Copyright](#copyright)
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- [Licensing information](#licenciung-informatrion)
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- [Funding](#funding)
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## Dataset Description
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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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The dataset can be used to train a model for Multilingual Machine Translation. Success on this task is typically measured by achieving a high BLEU score.
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### Languages
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The texts in the dataset are in Catalan and Italian.
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## Dataset Structure
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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 9.892.953 Italian sentences.
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### Data Splits
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The dataset contains a single split: `train`.
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## Dataset Creation
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### Source Data
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The dataset is a combination of the following authentic datasets:
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| Dataset | Sentences |
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|---------------|-----------|
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All corpora except Europarl were collected from [Opus](https://opus.nlpl.eu/).
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The Europarl corpus is a synthetic parallel corpus created from the original Spanish-Catalan corpus by [SoftCatalà](https://github.com/Softcatala/Europarl-catalan).
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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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No anonymisation process was performed.
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## Considerations for Using the Data
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### Social Impact of Dataset
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The purpose of this dataset is to help develop Machines Translation tasks for low-resource languages such as Catalan.
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### Discussion of Biases
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We are aware that since part of the data comes from unreliable web pages and non-curated texts, some biases may be present in the dataset.
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Nonetheless, we have not applied any steps to reduce their impact.
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### Other Known Limitations
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The dataset contains data of a general domain. Application of this dataset in more specific domains such as biomedical, legal etc. would be of limited use.
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## Additional Information
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### Author
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Language Technologies Unit (LangTech) at the Barcelona Supercomputing Center.
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### Contact information
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For further information, please send an email to [email protected].
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### Copyright
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Copyright Language Technologies Unit at Barcelona Supercomputing Center (2023).
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### Licensing information
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This work is licensed under a [Attribution-NonCommercial-ShareAlike 4.0 International](https://creativecommons.org/licenses/by-nc-sa/4.0/).
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### Funding
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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](https://politiquesdigitals.gencat.cat/ca/inici/index.html#googtrans(ca|en) within the framework of [Projecte AINA](https://politiquesdigitals.gencat.cat/ca/economia/catalonia-ai/aina).
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