Error code:   ConfigNamesError
Exception:    DataFilesNotFoundError
Message:      No (supported) data files found in projecte-aina/CA-FR_Parallel_Corpus
Traceback:    Traceback (most recent call last):
                File "/src/services/worker/src/worker/job_runners/dataset/config_names.py", line 66, in compute_config_names_response
                  config_names = get_dataset_config_names(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/inspect.py", line 347, in get_dataset_config_names
                  dataset_module = dataset_module_factory(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1873, in dataset_module_factory
                  raise e1 from None
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1854, in dataset_module_factory
                  return HubDatasetModuleFactoryWithoutScript(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 1245, in get_module
                  module_name, default_builder_kwargs = infer_module_for_data_files(
                File "/src/services/worker/.venv/lib/python3.9/site-packages/datasets/load.py", line 595, in infer_module_for_data_files
                  raise DataFilesNotFoundError("No (supported) data files found" + (f" in {path}" if path else ""))
              datasets.exceptions.DataFilesNotFoundError: No (supported) data files found in projecte-aina/CA-FR_Parallel_Corpus

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Dataset Card for CA-FR Parallel Corpus

Dataset Summary

The CA-FR Parallel Corpus is a Catalan-French dataset of 18.634.844 parallel sentences.The dataset was created to support Catalan in NLP tasks, specifically Machine Translation.

Supported Tasks and Leaderboards

The dataset can be used to train Bilingual Machine Translation models between French and Catalan in any direction, as well as Multilingual Machine Translation models.

Languages

The sentences included in the dataset are in Catalan (CA) and French (FR).

Dataset Structure

Data Instances

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

ca-fr_corpus.ca: contains 18.634.844 Catalan sentences.
ca-fr_corpus.fr: contains 18.634.844 French sentences.

Data Fields

[N/A]

Data Splits

The dataset contains a single split: train.

Dataset Creation

Curation Rationale

This dataset is aimed at promoting the development of Machine Translation between Catalan and other languages, specifically French.

Source Data

Initial Data Collection and Normalization

The dataset is a combination of the following original datasets:

Dataset	Sentences
CCMatrix	16.305.758
Multi CCAligned	1.442.584
WikiMatrix	437.665
GNOME	1.686
KDE 4	111.750
QED	52.797
TED 2020	44.101
Open Subtitles	225.786
Total	18.634.844

All corpora were collected from Opus.

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 18.634.844 parallel sentences.

Who are the source language producers?

Opus

Annotations

Annotation process

The dataset does not contain any annotations.

Who are the annotators?

[N/A]

Personal and Sensitive Information

Given that this dataset is partly derived from pre-existing datasets that may contain crawled data, and that no specific anonymisation process has been applied, personal and sensitive information may be present in the data. This needs to be considered when using the data for training models.

Considerations for Using the Data

Social Impact of Dataset

By providing this resource, we intend to promote the use of Catalan across NLP tasks, thereby improving the accessibility and visibility of the Catalan language.

Discussion of Biases

No specific bias mitigation strategies were applied to this dataset. Inherent biases may exist within the data.

Other Known Limitations

The dataset contains data of a general domain. Applications of this dataset in more specific domains such as biomedical, legal etc. would be of limited use.