Dataset Card for turkic_xwmt

Dataset Summary

To establish a comprehensive and challenging evaluation benchmark for Machine Translation in Turkic languages, we translate a test set originally introduced in WMT 2020 News Translation Task for English-Russian. The original dataset is profesionally translated and consists of sentences from news articles that are both English and Russian-centric. We adopt this evaluation set (X-WMT) and begin efforts to translate it into several Turkic languages. The current version of X-WMT includes covers 8 Turkic languages and 88 language directions with a minimum of 300 sentences per language direction.

Supported Tasks and Leaderboards

[More Information Needed]

Languages

Currently covered languages are (besides English and Russian):

• Azerbaijani (az)
• Bashkir (ba)
• Karakalpak (kaa)
• Kazakh (kk)
• Kirghiz (ky)
• Turkish (tr)
• Sakha (sah)
• Uzbek (uz)

Dataset Structure

Data Instances

A random example from the Russian-Uzbek set:

{"translation": {'ru': 'Моника Мутсвангва , министр информации Зимбабве , утверждает , что полиция вмешалась в отъезд Магомбейи из соображений безопасности и вследствие состояния его здоровья .', 'uz': 'Zimbabvening Axborot vaziri , Monika Mutsvanva Magombeyining xavfsizligi va sog'ligi tufayli bo'lgan jo'nab ketishinida politsiya aralashuvini ushlab turadi .'}}

Data Fields

Each example has one field "translation" that contains two subfields: one per language, e.g. for the Russian-Uzbek set:

• translation: a dictionary with two subfields:
  • ru: the russian text
  • uz: the uzbek text

Data Splits

Dataset Creation

Curation Rationale

[More Information Needed]

Source Data

Initial Data Collection and Normalization

[More Information Needed]

Who are the source language producers?

[More Information Needed]

Annotations

Annotation process

[More Information Needed]

Who are the annotators?

Translators, annotators and dataset contributors (in alphabetical order)

Abilxayr Zholdybai
Aigiz Kunafin
Akylbek Khamitov
Alperen Cantez
Aydos Muxammadiyarov
Doniyorbek Rafikjonov
Erkinbek Vokhabov
Ipek Baris
Iskander Shakirov
Madina Zokirjonova
Mohiyaxon Uzoqova
Mukhammadbektosh Khaydarov
Nurlan Maharramli
Petr Popov
Rasul Karimov
Sariya Kagarmanova
Ziyodabonu Qobiljon qizi

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

MIT License

Citation Information

@inproceedings{mirzakhalov2021large,
  title={A Large-Scale Study of Machine Translation in Turkic Languages},
  author={Mirzakhalov, Jamshidbek and Babu, Anoop and Ataman, Duygu and Kariev, Sherzod and Tyers, Francis and Abduraufov, Otabek and Hajili, Mammad and Ivanova, Sardana and Khaytbaev, Abror and Laverghetta Jr, Antonio and others},
  booktitle={Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing},
  pages={5876--5890},
  year={2021}
}

Contributions

This project was carried out with the help and contributions from dozens of individuals and organizations. We acknowledge and greatly appreciate each and every one of them:

Authors on the publications (in alphabetical order)

Abror Khaytbaev
Ahsan Wahab
Aigiz Kunafin
Anoop Babu
Antonio Laverghetta Jr.
Behzodbek Moydinboyev
Dr. Duygu Ataman
Esra Onal
Dr. Francis Tyers
Jamshidbek Mirzakhalov
Dr. John Licato
Dr. Julia Kreutzer
Mammad Hajili
Mokhiyakhon Uzokova
Dr. Orhan Firat
Otabek Abduraufov
Sardana Ivanova
Shaxnoza Pulatova
Sherzod Kariev
Dr. Sriram Chellappan

Translators, annotators and dataset contributors (in alphabetical order)

Abilxayr Zholdybai
Aigiz Kunafin
Akylbek Khamitov
Alperen Cantez
Aydos Muxammadiyarov
Doniyorbek Rafikjonov
Erkinbek Vokhabov
Ipek Baris
Iskander Shakirov
Madina Zokirjonova
Mohiyaxon Uzoqova
Mukhammadbektosh Khaydarov
Nurlan Maharramli
Petr Popov
Rasul Karimov
Sariya Kagarmanova
Ziyodabonu Qobiljon qizi

Industry supporters

Google Cloud
Khan Academy Oʻzbek
The Foundation for the Preservation and Development of the Bashkir Language

Thanks to @mirzakhalov for adding this dataset.