Datasets:

qanastek
/

ELRC-Medical-V2

	---
	annotations_creators:
	- machine-generated
	- expert-generated
	language_creators:
	- found
	language:
	- en
	- bg
	- cs
	- da
	- de
	- el
	- es
	- et
	- fi
	- fr
	- ga
	- hr
	- hu
	- it
	- lt
	- lv
	- mt
	- nl
	- pl
	- pt
	- ro
	- sk
	- sl
	- sv
	multilinguality:
	- multilingual
	pretty_name: ELRC-Medical-V2
	size_categories:
	- 100K<n<1M
	source_datasets:
	- extended
	task_categories:
	- translation
	task_ids:
	- translation
	---

	# ELRC-Medical-V2 : European parallel corpus for healthcare machine translation

	## Table of Contents
	- [Dataset Card for [Needs More Information]](#dataset-card-for-needs-more-information)
	- [Table of Contents](#table-of-contents)
	- [Dataset Description](#dataset-description)
	- [Dataset Summary](#dataset-summary)
	- [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards)
	- [Languages](#languages)
	- [Dataset Structure](#dataset-structure)
	- [Data Instances](#data-instances)
	- [Data Fields](#data-fields)
	- [Data Splits](#data-splits)
	- [Dataset Creation](#dataset-creation)
	- [Curation Rationale](#curation-rationale)
	- [Source Data](#source-data)
	- [Initial Data Collection and Normalization](#initial-data-collection-and-normalization)
	- [Who are the source language producers?](#who-are-the-source-language-producers)
	- [Personal and Sensitive Information](#personal-and-sensitive-information)
	- [Considerations for Using the Data](#considerations-for-using-the-data)
	- [Other Known Limitations](#other-known-limitations)
	- [Additional Information](#additional-information)
	- [Dataset Curators](#dataset-curators)
	- [Licensing Information](#licensing-information)
	- [Citation Information](#citation-information)

	## Dataset Description

	- Homepage: https://live.european-language-grid.eu/catalogue/project/2209
	- Repository: https://github.com/qanastek/ELRC-Medical-V2/
	- Paper: [Needs More Information]
	- Leaderboard: [Needs More Information]
	- Point of Contact: [Yanis Labrak](mailto:yanis.labrak@univ-avignon.fr)






	### Dataset Summary

	`ELRC-Medical-V2` is a parallel corpus for neural machine translation funded by the [European Commission](http://www.lr-coordination.eu/) and coordinated by the [German Research Center for Artificial Intelligence](https://www.dfki.de/web).

	### Supported Tasks and Leaderboards

	`translation`: The dataset can be used to train a model for translation.

	### Languages

	In our case, the corpora consists of a pair of source and target sentences for 23 differents languages from the European Union (EU) with as source language in each cases english (EN).

	List of languages : `Bulgarian (bg)`,`Czech (cs)`,`Danish (da)`,`German (de)`,`Greek (el)`,`Spanish (es)`,`Estonian (et)`,`Finnish (fi)`,`French (fr)`,`Irish (ga)`,`Croatian (hr)`,`Hungarian (hu)`,`Italian (it)`,`Lithuanian (lt)`,`Latvian (lv)`,`Maltese (mt)`,`Dutch (nl)`,`Polish (pl)`,`Portuguese (pt)`,`Romanian (ro)`,`Slovak (sk)`,`Slovenian (sl)`,`Swedish (sv)`.

	## Load the dataset with HuggingFace

	```python
	from datasets import load_dataset

	NAME = "qanastek/ELRC-Medical-V2"

	dataset = load_dataset(NAME, use_auth_token=True)
	print(dataset)

	dataset_train = load_dataset(NAME, "en-es", split='train[:90%]')
	dataset_test = load_dataset(NAME, "en-es", split='train[10%:]')
	print(dataset_train)
	print(dataset_train[0])
	print(dataset_test)
	```

	## Dataset Structure

	### Data Instances

	```plain
	id,lang,source_text,target_text
	1,en-bg,"TOC \o ""1-3"" \h \z \u Introduction 3","TOC \o ""1-3"" \h \z \u Въведение 3"
	2,en-bg,The international humanitarian law and its principles are often not respected.,Международното хуманитарно право и неговите принципи често не се зачитат.
	3,en-bg,"At policy level, progress was made on several important initiatives.",На равнище политики напредък е постигнат по няколко важни инициативи.
	```

	### Data Fields

	id : The document identifier of type `Integer`.

	lang : The pair of source and target language of type `String`.

	source_text : The source text of type `String`.

	target_text : The target text of type `String`.

	### Data Splits

	\| Lang \| # Docs \| Avg. # Source Tokens \| Avg. # Target Tokens \|
	\|--------\|-----------\|------------------------\|------------------------\|
	\| bg \| 13 149 \| 23 \| 24 \|
	\| cs \| 13 160 \| 23 \| 21 \|
	\| da \| 13 242 \| 23 \| 22 \|
	\| de \| 13 291 \| 23 \| 22 \|
	\| el \| 13 091 \| 23 \| 26 \|
	\| es \| 13 195 \| 23 \| 28 \|
	\| et \| 13 016 \| 23 \| 17 \|
	\| fi \| 12 942 \| 23 \| 16 \|
	\| fr \| 13 149 \| 23 \| 28 \|
	\| ga \| 412 \| 12 \| 12 \|
	\| hr \| 12 836 \| 23 \| 21 \|
	\| hu \| 13 025 \| 23 \| 21 \|
	\| it \| 13 059 \| 23 \| 25 \|
	\| lt \| 12 580 \| 23 \| 18 \|
	\| lv \| 13 044 \| 23 \| 19 \|
	\| mt \| 3 093 \| 16 \| 14 \|
	\| nl \| 13 191 \| 23 \| 25 \|
	\| pl \| 12 761 \| 23 \| 22 \|
	\| pt \| 13 148 \| 23 \| 26 \|
	\| ro \| 13 163 \| 23 \| 25 \|
	\| sk \| 12 926 \| 23 \| 20 \|
	\| sl \| 13 208 \| 23 \| 21 \|
	\| sv \| 13 099 \| 23 \| 21 \|
	\|\|\|\|\|
	\| Total \| 277 780 \| 22.21 \| 21.47 \|

	## Dataset Creation

	### Curation Rationale

	For details, check the corresponding [pages](https://elrc-share.eu/repository/search/?q=mfsp%3A87ef9e5e8ac411ea913100155d026706e19a1a9f908b463c944490c36ba2f454&page=3).

	### Source Data

	#### Initial Data Collection and Normalization

	The acquisition of bilingual data (from multilingual websites), normalization, cleaning, deduplication and identification of parallel documents have been done by [ILSP-FC tool](http://nlp.ilsp.gr/redmine/projects/ilsp-fc/wiki/Introduction). [Maligna aligner](https://github.com/loomchild/maligna) was used for alignment of segments. Merging/filtering of segment pairs has also been applied.

	#### Who are the source language producers?

	Every data of this corpora as been uploaded by [Vassilis Papavassiliou](mailto:vpapa@ilsp.gr) on [ELRC-Share](https://elrc-share.eu/repository/browse/bilingual-corpus-from-the-publications-office-of-the-eu-on-the-medical-domain-v2-en-fr/6b31b32e8ac411ea913100155d0267061547d9b3ec284584af19a2953baa8937/).

	### Personal and Sensitive Information

	The corpora is free of personal or sensitive information.

	## Considerations for Using the Data

	### Other Known Limitations

	The nature of the task introduce a variability in the quality of the target translations.

	## Additional Information

	### Dataset Curators

	__ELRC-Medical-V2__: Labrak Yanis, Dufour Richard

	__Bilingual corpus from the Publications Office of the EU on the medical domain v.2 (EN-XX) Corpus__: [Vassilis Papavassiliou](mailto:vpapa@ilsp.gr) and [others](https://live.european-language-grid.eu/catalogue/project/2209).

	### Licensing Information

	<a rel="license" href="https://elrc-share.eu/static/metashare/licences/CC-BY-4.0.pdf"><img alt="Attribution 4.0 International (CC BY 4.0) License" style="border-width:0" src="https://i.creativecommons.org/l/by/4.0/88x31.png" /></a><br />This work is licensed under a <a rel="license" href="https://elrc-share.eu/static/metashare/licences/CC-BY-4.0.pdf">Attribution 4.0 International (CC BY 4.0) License</a>.

	### Citation Information

	Please cite the following paper when using this model.

	```latex
	@inproceedings{losch-etal-2018-european,
	title = European Language Resource Coordination: Collecting Language Resources for Public Sector Multilingual Information Management,
	author = {
	L'osch, Andrea and
	Mapelli, Valérie and
	Piperidis, Stelios and
	Vasiljevs, Andrejs and
	Smal, Lilli and
	Declerck, Thierry and
	Schnur, Eileen and
	Choukri, Khalid and
	van Genabith, Josef
	},
	booktitle = Proceedings of the Eleventh International Conference on Language Resources and Evaluation (LREC 2018),
	month = may,
	year = 2018,
	address = Miyazaki, Japan,
	publisher = European Language Resources Association (ELRA),
	url = https://aclanthology.org/L18-1213,
	}
	```