Datasets:
				
			
			
	
			
			
	
		
		annotations_creators:
  - found
language_creators:
  - found
language:
  - af
  - am
  - ar
  - ast
  - az
  - be
  - bg
  - bn
  - br
  - ca
  - ceb
  - cs
  - cy
  - da
  - de
  - el
  - en
  - eo
  - es
  - et
  - eu
  - fa
  - fi
  - fr
  - fy
  - ga
  - gd
  - gl
  - ha
  - he
  - hi
  - hr
  - hu
  - hy
  - id
  - ig
  - ilo
  - is
  - it
  - ja
  - jv
  - ka
  - kk
  - km
  - ko
  - la
  - lb
  - lg
  - lt
  - lv
  - mg
  - mk
  - ml
  - mr
  - ms
  - my
  - ne
  - nl
  - 'no'
  - oc
  - om
  - or
  - pl
  - pt
  - ro
  - ru
  - sd
  - si
  - sk
  - sl
  - so
  - sq
  - sr
  - su
  - sv
  - sw
  - ta
  - tl
  - tr
  - tt
  - uk
  - ur
  - uz
  - vi
  - wo
  - xh
  - yi
  - yo
  - zh
  - zu
  - se
license:
  - unknown
multilinguality:
  - multilingual
size_categories:
  - 100M<n<1B
source_datasets:
  - original
task_categories:
  - text2text-generation
  - translation
task_ids: []
paperswithcode_id: ccmatrix
pretty_name: CCMatrixV1
tags:
  - conditional-text-generation
Dataset Card for CCMatrix v1
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage: https://opus.nlpl.eu/CCMatrix.php
- Repository: None
- Paper: https://arxiv.org/abs/1911.04944
Dataset Summary
This corpus has been extracted from web crawls using the margin-based bitext mining techniques described at https://github.com/facebookresearch/LASER/tree/master/tasks/CCMatrix.
- 90 languages, 1,197 bitexts
- total number of files: 90
- total number of tokens: 112.14G
- total number of sentence fragments: 7.37G
Supported Tasks and Leaderboards
[More Information Needed]
Languages
Configs are generated for all language pairs in both directions. You can find the valid pairs in Homepage section of Dataset Description: https://opus.nlpl.eu/CCMatrix.php E.g.
from datasets import load_dataset
dataset = load_dataset("yhavinga/ccmatrix", "en-nl", streaming=True)
This will open the en-nl dataset in streaming mode. Without streaming, download and prepare will take tens of minutes.
You can inspect elements with:
print(next(iter(dataset['train'])))
{'id': 0, 'score': 1.2499677, 'translation': {'en': 'They come from all parts of Egypt, just like they will at the day of His coming.', 'nl': 'Zij kwamen uit alle delen van Egypte, evenals zij op de dag van Zijn komst zullen doen.'}}
Dataset Structure
Data Instances
For example:
{
        "id": 1,
        "score": 1.2498379,
        "translation": {
            "nl": "En we moeten elke waarheid vals noemen die niet minstens door een lach vergezeld ging.”",
            "en": "And we should call every truth false which was not accompanied by at least one laugh.”"
        }
    }
Data Fields
Each example contains an integer id starting with 0, a score, and a translation dictionary with the language 1 and language 2 texts.
Data Splits
Only a train split is provided.
Dataset Creation
Curation Rationale
[More Information Needed]
Source Data
[More Information Needed]
Initial Data Collection and Normalization
[More Information Needed]
Who are the source language producers?
[More Information Needed]
Annotations
[More Information Needed]
Annotation process
[More Information Needed]
Who are the annotators?
[More Information Needed]
Personal and Sensitive Information
[More Information Needed]
Considerations for Using the Data
Social Impact of Dataset
[More Information Needed]
Discussion of Biases
[More Information Needed]
Other Known Limitations
[More Information Needed]
Additional Information
Dataset Curators
[More Information Needed]
Licensing Information
[More Information Needed]
Citation Information
IMPORTANT: Please cite reference [2][3] if you use this data.
- CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Data by Guillaume Wenzek, Marie-Anne Lachaux, Alexis Conneau, Vishrav Chaudhary, Francisco Guzmán, Armand Jouli and Edouard Grave.
- CCMatrix: Mining Billions of High-Quality Parallel Sentences on the WEB by Holger Schwenk, Guillaume Wenzek, Sergey Edunov, Edouard Grave and Armand Joulin.
- Beyond English-Centric Multilingual Machine Translation by Angela Fan, Shruti Bhosale, Holger Schwenk, Zhiyi Ma, Ahmed El-Kishky, Siddharth Goyal, Mandeep Baines, Onur Celebi, Guillaume Wenzek, Vishrav Chaudhary, Naman Goyal, Tom Birch, Vitaliy Liptchinsky, Sergey Edunov, Edouard Grave, Michael Auli, and Armand Joulin.
This HuggingFace CCMatrix dataset is a wrapper around the service and files prepared and hosted by OPUS:
- Parallel Data, Tools and Interfaces in OPUS by Jörg Tiedemann.
