Datasets:
annotations_creators:
- expert-generated
language_creators:
- expert-generated
language:
- bg
- cs
- da
- de
- el
- en
- es
- et
- fi
- fr
- hr
- hu
- is
- it
- lt
- lv
- mt
- nl
- 'no'
- pl
- pt
- ro
- sk
- sl
- sv
- tr
license:
- cc-by-4.0
multilinguality:
- translation
size_categories:
- 1K<n<10K
source_datasets:
- original
task_categories:
- translation
task_ids: []
pretty_name: Europa Education and Culture Translation Memory (EAC-TM)
dataset_info:
- config_name: en2bg
features:
- name: translation
dtype:
translation:
languages:
- en
- bg
- name: sentence_type
dtype:
class_label:
names:
'0': form_data
'1': sentence_data
splits:
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- config_name: en2cs
features:
- name: translation
dtype:
translation:
languages:
- en
- cs
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dtype:
class_label:
names:
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'1': sentence_data
splits:
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download_size: 3521416
dataset_size: 365983
- config_name: en2da
features:
- name: translation
dtype:
translation:
languages:
- en
- da
- name: sentence_type
dtype:
class_label:
names:
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'1': sentence_data
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- config_name: en2de
features:
- name: translation
dtype:
translation:
languages:
- en
- de
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dtype:
class_label:
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'1': sentence_data
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- config_name: en2el
features:
- name: translation
dtype:
translation:
languages:
- en
- el
- name: sentence_type
dtype:
class_label:
names:
'0': form_data
'1': sentence_data
splits:
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download_size: 3521416
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- config_name: en2es
features:
- name: translation
dtype:
translation:
languages:
- en
- es
- name: sentence_type
dtype:
class_label:
names:
'0': form_data
'1': sentence_data
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- config_name: en2et
features:
- name: translation
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translation:
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- en
- et
- name: sentence_type
dtype:
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- config_name: en2fi
features:
- name: translation
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translation:
languages:
- en
- fi
- name: sentence_type
dtype:
class_label:
names:
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download_size: 3521416
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- config_name: en2fr
features:
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- config_name: en2hu
features:
- name: translation
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translation:
languages:
- en
- hu
- name: sentence_type
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- config_name: en2is
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- config_name: en2it
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- en
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- name: sentence_type
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- config_name: en2lt
features:
- name: translation
dtype:
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languages:
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- lt
- name: sentence_type
dtype:
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- config_name: en2lv
features:
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- en
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- name: sentence_type
dtype:
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- name: train
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- config_name: en2mt
features:
- name: translation
dtype:
translation:
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- en
- mt
- name: sentence_type
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- name: train
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download_size: 3521416
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- config_name: en2nb
features:
- name: translation
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translation:
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- en
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- name: sentence_type
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- config_name: en2nl
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- config_name: en2pl
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- config_name: en2pt
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- name: translation
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- config_name: en2ro
features:
- name: translation
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- name: sentence_type
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- name: train
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- config_name: en2sk
features:
- name: translation
dtype:
translation:
languages:
- en
- sk
- name: sentence_type
dtype:
class_label:
names:
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- name: train
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download_size: 3521416
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- config_name: en2sl
features:
- name: translation
dtype:
translation:
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- en
- sl
- name: sentence_type
dtype:
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download_size: 3521416
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- config_name: en2sv
features:
- name: translation
dtype:
translation:
languages:
- en
- sv
- name: sentence_type
dtype:
class_label:
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'1': sentence_data
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- name: train
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download_size: 3521416
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- config_name: en2tr
features:
- name: translation
dtype:
translation:
languages:
- en
- tr
- name: sentence_type
dtype:
class_label:
names:
'0': form_data
'1': sentence_data
splits:
- name: train
num_bytes: 328267
num_examples: 3198
download_size: 3521416
dataset_size: 328267
configs:
- config_name: en2bg
data_files:
- split: train
path: en2bg/train-*
- config_name: en2es
data_files:
- split: train
path: en2es/train-*
- config_name: en2fr
data_files:
- split: train
path: en2fr/train-*
Dataset Card for Europa Education and Culture Translation Memory (EAC-TM)
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/eac-translation-memory
- Paper: https://link.springer.com/article/10.1007/s10579-014-9277-0
- Point of Contact: ralf.steinberg@jrc.ec.europa.eu
Dataset Summary
This dataset is a corpus of manually produced translations from english to up to 25 languages, released in 2012 by the European Union's Directorate General for Education and Culture (EAC).
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_eac_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
The sentences in this dataset were originally written in English (source language is English) and then translated into the other languages. The sentences are extracted from electroniv forms: application and report forms for decentralised actions of EAC's Life-long Learning Programme (LLP) and the Youth in Action Programme. The contents in the electronic forms are technically split into two types: (a) the labels and contents of drop-down menus (referred to as 'Forms' Data) and (b) checkboxes (referred to as 'Reference Data').
The dataset contains traduction of English sentences or parts of sentences to Bulgarian, Czech, Danish, Dutch, Estonian, German, Greek, Finnish, French, Croatian, Hungarian, Icelandic, Italian, Latvian, Lithuanian, Maltese, Norwegian, Polish, Portuguese, Romanian, Slovak, Slovenian, Spanish, Swedish and Turkish.
Language codes:
bgcsdadeelenesetfifrhrhuisitltlvmtnlnoplptroskslsvtr
Dataset Structure
Data Instances
{
"translation": {
"en":"Sentence to translate",
"<target_language>": "Phrase à traduire",
},
"sentence_type": 0
}
Data Fields
translation: Mapping of sentences to translate (in English) and translated sentences.sentence_type: Integer value, 0 if the sentence is a 'form data' (extracted from the labels and contents of drop-down menus of the source electronic forms) or 1 if the sentence is a 'reference data' (extracted from the electronic forms checkboxes).
Data Splits
The data is not splitted (only the train split is available).
Dataset Creation
Curation Rationale
The EAC-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 education and culture. Also, it includes translation units for the languages Croatian (HR), Icelandic (IS), Norwegian (Bokmål, NB or Norwegian, NO) and Turkish (TR).
Source Data
Initial Data Collection and Normalization
EAC-TM was built in the context of translating electronic forms: application and report forms for decentralised actions of EAC's Life-long Learning Programme (LLP) and the Youth in Action Programme. All documents and sentences were originally written in English (source language is English) and then translated into the other languages.
The contents in the electronic forms are technically split into two types: (a) the labels and contents of drop-down menus (referred to as 'Forms' Data) and (b) checkboxes (referred to as 'Reference Data'). Due to the different types of data, the two collections are kept separate. For example, labels can be 'Country', 'Please specify your home country' etc., while examples for reference data are 'Germany', 'Basic/general programmes', 'Education and Culture' etc.
The data consists of translations carried out between the end of the year 2008 and July 2012.
Who are the source language producers?
The texts were translated by staff of the National Agencies of the Lifelong Learning and Youth in Action programmes. They are typically professionals in the field of education/youth and EU programmes. They are thus not professional translators, but they are normally native speakers of the target language.
Annotations
Annotation process
Sentences were manually translated by humans.
Who are the annotators?
The texts were translated by staff of the National Agencies of the Lifelong Learning and Youth in Action programmes. They are typically professionals in the field of education/youth and EU programmes. They are thus not professional translators, but they are normally native speakers of the target language.
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
© European Union, 1995-2020
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Unless otherwise indicated (e.g. in individual copyright notices), content owned by the EU on this website is licensed under the Creative Commons Attribution 4.0 International (CC BY 4.0) licence. This means that reuse is allowed, provided appropriate credit is given and changes are indicated.
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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.