Datasets:
language:
- ca
- eu
- multilingual
multilinguality:
- translation
pretty_name: CA-EU Parallel Corpus
size_categories:
- 1M<n<10M
source_datasets:
- original
task_categories:
- translation
task_ids: []
Dataset Card for CA-EU Parallel Corpus
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
Dataset Summary
The CA-EU Parallel Corpus is a Catalan-Basque synthetic dataset of 9.692.996 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 Basque.
Dataset Structure
Two separated txt files are provided with the sentences sorted in the same order:
train_clean.ca: contains 9.692.996 Catalan sentences.
train_clean.eu: contains 9.692.996 Basque sentences.
Data Splits
The dataset contains a single split: train.
Dataset Creation
Source Data
This synthetic dataset was created in the frame of Project Ilenia. An authentic parallel corpus ES-EU was delivered by Project GAITU and the Spanish was translated to Catalan using the machine translation model PlanTL-GOB-ES.
Total: 9.692.996 parallel sentences .
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 [email protected].
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 SEDIA within the framework of ILENIA.