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Dataset Card for "para_crawl"
Dataset Summary
Web-Scale Parallel Corpora for Official European Languages.
Supported Tasks and Leaderboards
Languages
Dataset Structure
Data Instances
enbg
- Size of downloaded dataset files: 103.75 MB
- Size of the generated dataset: 356.54 MB
- Total amount of disk used: 460.27 MB
An example of 'train' looks as follows.
This example was too long and was cropped:
{
"translation": "{\"bg\": \". “A felirat faragott karnis a bejárat fölött, templom épült 14 Július 1643, A földesúr és felesége Jeremiás Murguleţ, C..."
}
encs
- Size of downloaded dataset files: 196.41 MB
- Size of the generated dataset: 638.07 MB
- Total amount of disk used: 834.48 MB
An example of 'train' looks as follows.
This example was too long and was cropped:
{
"translation": "{\"cs\": \". “A felirat faragott karnis a bejárat fölött, templom épült 14 Július 1643, A földesúr és felesége Jeremiás Murguleţ, C..."
}
enda
- Size of downloaded dataset files: 182.81 MB
- Size of the generated dataset: 598.62 MB
- Total amount of disk used: 781.43 MB
An example of 'train' looks as follows.
This example was too long and was cropped:
{
"translation": "{\"da\": \". “A felirat faragott karnis a bejárat fölött, templom épült 14 Július 1643, A földesúr és felesége Jeremiás Murguleţ, C..."
}
ende
- Size of downloaded dataset files: 1.31 GB
- Size of the generated dataset: 4.00 GB
- Total amount of disk used: 5.30 GB
An example of 'train' looks as follows.
This example was too long and was cropped:
{
"translation": "{\"de\": \". “A felirat faragott karnis a bejárat fölött, templom épült 14 Július 1643, A földesúr és felesége Jeremiás Murguleţ, C..."
}
enel
- Size of downloaded dataset files: 193.56 MB
- Size of the generated dataset: 688.07 MB
- Total amount of disk used: 881.62 MB
An example of 'train' looks as follows.
This example was too long and was cropped:
{
"translation": "{\"el\": \". “A felirat faragott karnis a bejárat fölött, templom épült 14 Július 1643, A földesúr és felesége Jeremiás Murguleţ, C..."
}
Data Fields
The data fields are the same among all splits.
enbg
translation
: a multilingualstring
variable, with possible languages includingen
,bg
.
encs
translation
: a multilingualstring
variable, with possible languages includingen
,cs
.
enda
translation
: a multilingualstring
variable, with possible languages includingen
,da
.
ende
translation
: a multilingualstring
variable, with possible languages includingen
,de
.
enel
translation
: a multilingualstring
variable, with possible languages includingen
,el
.
Data Splits
name | train |
---|---|
enbg | 1039885 |
encs | 2981949 |
enda | 2414895 |
ende | 16264448 |
enel | 1985233 |
Dataset Creation
Curation Rationale
Source Data
Initial Data Collection and Normalization
Who are the source language producers?
Annotations
Annotation process
Who are the annotators?
Personal and Sensitive Information
Considerations for Using the Data
Social Impact of Dataset
Discussion of Biases
Other Known Limitations
Additional Information
Dataset Curators
Licensing Information
Creative Commons CC0 license ("no rights reserved").
Citation Information
@inproceedings{banon-etal-2020-paracrawl,
title = "{P}ara{C}rawl: Web-Scale Acquisition of Parallel Corpora",
author = "Ba{\~n}{\'o}n, Marta and
Chen, Pinzhen and
Haddow, Barry and
Heafield, Kenneth and
Hoang, Hieu and
Espl{\`a}-Gomis, Miquel and
Forcada, Mikel L. and
Kamran, Amir and
Kirefu, Faheem and
Koehn, Philipp and
Ortiz Rojas, Sergio and
Pla Sempere, Leopoldo and
Ram{\'\i}rez-S{\'a}nchez, Gema and
Sarr{\'\i}as, Elsa and
Strelec, Marek and
Thompson, Brian and
Waites, William and
Wiggins, Dion and
Zaragoza, Jaume",
booktitle = "Proceedings of the 58th Annual Meeting of the Association for Computational Linguistics",
month = jul,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.acl-main.417",
doi = "10.18653/v1/2020.acl-main.417",
pages = "4555--4567",
abstract = "We report on methods to create the largest publicly available parallel corpora by crawling the web, using open source software. We empirically compare alternative methods and publish benchmark data sets for sentence alignment and sentence pair filtering. We also describe the parallel corpora released and evaluate their quality and their usefulness to create machine translation systems.",
}
Contributions
Thanks to @thomwolf, @lewtun, @patrickvonplaten, @mariamabarham for adding this dataset.
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