Datasets:
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- bg
- cs
- da
- de
- el
- en
- es
- et
- fi
- fr
- ga
- hu
- is
- it
- lt
- lv
- mt
- nl
- 'no'
- pl
- pt
- ro
- sk
- sl
- sv
license:
- cc-by-sa-4.0
multilinguality:
- translation
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- translation
task_ids: []
paperswithcode_id: null
pretty_name: EuropaEcdcTm
dataset_info:
- config_name: en2bg
features:
- name: translation
dtype:
translation:
languages:
- en
- bg
splits:
- name: train
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num_examples: 2567
download_size: 4286636
dataset_size: 798444
- config_name: en2cs
features:
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dtype:
translation:
languages:
- en
- cs
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- config_name: en2da
features:
- name: translation
dtype:
translation:
languages:
- en
- da
splits:
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download_size: 4286636
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- config_name: en2de
features:
- name: translation
dtype:
translation:
languages:
- en
- de
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- config_name: en2el
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- name: translation
dtype:
translation:
languages:
- en
- el
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- config_name: en2es
features:
- name: translation
dtype:
translation:
languages:
- en
- es
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- config_name: en2et
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translation:
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- en
- et
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- name: train
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download_size: 4286636
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- config_name: en2fi
features:
- name: translation
dtype:
translation:
languages:
- en
- fi
splits:
- name: train
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download_size: 4286636
dataset_size: 573069
- config_name: en2fr
features:
- name: translation
dtype:
translation:
languages:
- en
- fr
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- name: train
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download_size: 4286636
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- config_name: en2ga
features:
- name: translation
dtype:
translation:
languages:
- en
- ga
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- name: train
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- config_name: en2hu
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- name: translation
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translation:
languages:
- en
- hu
splits:
- name: train
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num_examples: 2571
download_size: 4286636
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- config_name: en2is
features:
- name: translation
dtype:
translation:
languages:
- en
- is
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- name: train
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translation:
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- en
- lt
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- name: train
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- config_name: en2lv
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- name: translation
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translation:
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- en
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- name: translation
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translation:
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- en
- mt
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- name: train
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translation:
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- en
- nl
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translation:
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- en
- 'no'
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- name: train
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- config_name: en2pl
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- name: translation
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- en
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- config_name: en2pt
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- name: translation
dtype:
translation:
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- en
- pt
splits:
- name: train
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- config_name: en2ro
features:
- name: translation
dtype:
translation:
languages:
- en
- ro
splits:
- name: train
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download_size: 4286636
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- config_name: en2sk
features:
- name: translation
dtype:
translation:
languages:
- en
- sk
splits:
- name: train
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download_size: 4286636
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- config_name: en2sl
features:
- name: translation
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translation:
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- en
- sl
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- name: train
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- config_name: en2sv
features:
- name: translation
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translation:
languages:
- en
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splits:
- name: train
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Dataset Card for [Dataset Name]
Table of Contents
- Dataset Description
- Dataset Structure
- Dataset Creation
- Considerations for Using the Data
- Additional Information
Dataset Description
- Homepage: https://ec.europa.eu/jrc/en/language-technologies/ecdc-translation-memory
- Paper: https://link.springer.com/article/10.1007/s10579-014-9277-0
- Point of Contact: Ralf Steinberger
Dataset Summary
In October 2012, the European Union (EU) agency 'European Centre for Disease Prevention and Control' (ECDC) released a translation memory (TM), i.e. a collection of sentences and their professionally produced translations, in twenty-five languages.
ECDC-TM covers 25 languages: the 23 official languages of the EU plus Norwegian (Norsk) and Icelandic. ECDC-TM was created by translating from English into the following 24 languages: Bulgarian, Czech, Danish, Dutch, English, Estonian, Gaelige (Irish), German, Greek, Finnish, French, Hungarian, Icelandic, Italian, Latvian, Lithuanian, Maltese, Norwegian (NOrsk), Polish, Portuguese, Romanian, Slovak, Slovenian, Spanish and Swedish.
All documents and sentences were originally written in English. They were then translated into the other languages by professional translators from the Translation Centre CdT in Luxembourg.
To load a language pair that is not part of the config, just specify the language code as language pair. For example, if you want to translate Czech to Greek:
dataset = load_dataset("europa_ecdc_tm", language_pair=("cs", "el"))
Supported Tasks and Leaderboards
text2text-generation
: the dataset can be used to train a model formachine-translation
. Machine translation models are usually evaluated using metrics such as BLEU, ROUGE or SacreBLEU. You can use the mBART model for this task. This task has active leaderboards which can be found at https://paperswithcode.com/task/machine-translation, which usually rank models based on BLEU score.
Languages
All documents and sentences were originally written in English (en
). They were then translated into the other languages by professional translators from the Translation Centre CdT in Luxembourg.
Translations are available in these languages: en
, bg
, cs
, da
, de
, el
, en
, es
, et
, fi
, fr
, ga
, hu
, is
, it
, lt
, lv
, mt
, nl
, no
, pl
, pt
, ro
, sk
, sl
, sv
.
Dataset Structure
Data Instances
{
"translation": {
"<source_language>":"Sentence to translate",
"<target_language>": "Translated sentence",
},
}
Data Fields
translation
: a multilingualstring
variable, with possible languages includingen
,bg
,cs
,da
,de
,el
,en
,es
,et
,fi
,fr
,ga
,hu
,is
,it
,lt
,lv
,mt
,nl
,no
,pl
,pt
,ro
,sk
,sl
,sv
.
Data Splits
The data is not splitted (only the train
split is available).
Dataset Creation
Curation Rationale
The ECDC-TM is relatively small compared to the JRC-Acquis and to DGT-TM, but it has the advantage that it focuses on a very different domain, namely that of public health. Also, it includes translation units for the languages Irish (Gaelige, GA), Norwegian (Norsk, NO) and Icelandic (IS).
Source Data
Initial Data Collection and Normalization
ECDC-TM was built on the basis of the website of the European Centre for Disease Prevention and Control (ECDC). The major part of the documents talks about health-related topics (anthrax, botulism, cholera, dengue fever, hepatitis, etc.), but some of the web pages also describe the organisation ECDC (e.g. its organisation, job opportunities) and its activities (e.g. epidemic intelligence, surveillance).
Who are the source language producers?
All documents and sentences were originally written in English, by the ECDC website content producers.
Annotations
Annotation process
[More Information Needed]
Who are the annotators?
All documents and sentences were thus originally written in English. They were then translated into the other languages by professional translators from the Translation Centre CdT in Luxembourg.
Personal and Sensitive Information
[More Information Needed]
Considerations for Using the Data
Social Impact of Dataset
Contains translations of sentences in the public healthcare domain, including technical terms (disease and treatment names for example).
Discussion of Biases
[More Information Needed]
Other Known Limitations
[More Information Needed]
Additional Information
Dataset Curators
[More Information Needed]
Licensing Information
Copyright © EU / ECDC, 2020
Copyright
The Work (as defined below) is provided under the terms of this Licence (or later versions of
this Licence published by the European Commission). The work is protected by copyright
and/or other applicable law. Any use of the work other than as authorised under this
Licence or copyright law is prohibited.
The terms provided herein conform to the reuse policy established by the Commission's
Reuse Decision (2011/833/EU).
By exercising any rights to the work provided here, you accept and agree to be bound by the
terms of this Licence. The Owner (as defined below) grants You the rights conferred by this
Licence in consideration of your acceptance of such terms and conditions.
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Citation Information
@Article{Steinberger2014,
author={Steinberger, Ralf
and Ebrahim, Mohamed
and Poulis, Alexandros
and Carrasco-Benitez, Manuel
and Schl{\"u}ter, Patrick
and Przybyszewski, Marek
and Gilbro, Signe},
title={An overview of the European Union's highly multilingual parallel corpora},
journal={Language Resources and Evaluation},
year={2014},
month={Dec},
day={01},
volume={48},
number={4},
pages={679-707},
issn={1574-0218},
doi={10.1007/s10579-014-9277-0},
url={https://doi.org/10.1007/s10579-014-9277-0}
}
Contributions
Thanks to @SBrandeis for adding this dataset.