README.md

metadata

language:
  - ca
  - de
  - multilingual
multilinguality:
  - translation
pretty_name: CA-DE Parallel Corpus
size_categories:
  - 1M<n<10M
source_datasets:
  - original
task_categories:
  - translation
task_ids: []

Dataset Card for CA-DE Parallel Corpus

Table of Contents

• Dataset Description
  • Dataset Summary
  • Supported Tasks
  • Languages
• Dataset Structure
  • Data Splits
• Dataset Creation
  • Source Data
  • Data preparation
  • Personal and Sensitive Information
• Considerations for Using the Data
  • Social Impact of Dataset
  • Discussion of Biases
  • Other Known Limitations
• Additional Information
  • Author
  • Contact Information
  • Copyright
  • Licensing information
  • Funding

Dataset Description

Dataset Summary

The CA-PT Parallel Corpus is a Catalan-German dataset of XXX parallel sentences. The dataset was created to support Catalan NLP tasks, e.g., Machine Translation.

Supported Tasks and Leaderboards

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.

Languages

The texts in the dataset are in Catalan and German.

Dataset Structure

Two separated txt files are provided with the sentences sorted in the same order:

• ca-de_all_2023_09_11.ca: contains XXX Catalan sentences.

• ca-de_all_2023_09_11.de: contains XXX German sentences.

Data Splits

The dataset contains a single split: train.

Dataset Creation

Source Data

The dataset is a combination of the following authentic datasets:

Dataset	Sentences

All corpora except Europarl were collected from Opus. The Europarl corpus is a synthetic parallel corpus created from the original Spanish-Catalan corpus by SoftCatalà.

The remaining XXX sentences are synthetic parallel data created from a random sampling of the Spanish-German corpora available on Opus and translated into Catalan using the PlanTL es-ca model.

Data preparation

All datasets are deduplicated and filtered to remove any sentence pairs with a cosine similarity of less than 0.75. This is done using sentence embeddings calculated using LaBSE. 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.

Personal and Sensitive Information

No anonymisation process was performed.

Considerations for Using the Data

Social Impact of Dataset

The purpose of this dataset is to help develop Machines Translation tasks for low-resource languages such as Catalan.

Discussion of Biases

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. Nonetheless, we have not applied any steps to reduce their impact.

Other Known Limitations

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.

Additional Information

Author

Language Technologies Unit (LangTech) at the Barcelona Supercomputing Center.

Contact information

For further information, please send an email to langtech@bsc.es.

Copyright

Copyright Language Technologies Unit at Barcelona Supercomputing Center (2023).

Licensing information

This work is licensed under a Attribution-NonCommercial-ShareAlike 4.0 International.

Funding

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.