---
annotations_creators:
- found
language_creators:
- found
language:
- ar
- en
- es
- fr
- ru
- zh
license: other
multilinguality:
- multilingual
size_categories:
- 10M<n<100M
source_datasets:
- original
task_categories:
- translation
task_ids: []
paperswithcode_id: united-nations-parallel-corpus
pretty_name: United Nations Parallel Corpus
config_names:
- ar-en
- ar-es
- ar-fr
- ar-ru
- ar-zh
- en-es
- en-fr
- en-ru
- en-zh
- es-fr
- es-ru
- es-zh
- fr-ru
- fr-zh
- ru-zh
dataset_info:
- config_name: ar-en
  features:
  - name: translation
    dtype:
      translation:
        languages:
        - ar
        - en
  splits:
  - name: train
    num_bytes: 8039673899
    num_examples: 20044478
  download_size: 3638378262
  dataset_size: 8039673899
- config_name: ar-es
  features:
  - name: translation
    dtype:
      translation:
        languages:
        - ar
        - es
  splits:
  - name: train
    num_bytes: 8715738416
    num_examples: 20532014
  download_size: 3938780664
  dataset_size: 8715738416
- config_name: ar-fr
  features:
  - name: translation
    dtype:
      translation:
        languages:
        - ar
        - fr
  splits:
  - name: train
    num_bytes: 8897831806
    num_examples: 20281645
  download_size: 3976788621
  dataset_size: 8897831806
- config_name: ar-ru
  features:
  - name: translation
    dtype:
      translation:
        languages:
        - ar
        - ru
  splits:
  - name: train
    num_bytes: 11395906619
    num_examples: 20571334
  download_size: 4836152717
  dataset_size: 11395906619
- config_name: ar-zh
  features:
  - name: translation
    dtype:
      translation:
        languages:
        - ar
        - zh
  splits:
  - name: train
    num_bytes: 6447644160
    num_examples: 17306056
  download_size: 3050491574
  dataset_size: 6447644160
- config_name: en-es
  features:
  - name: translation
    dtype:
      translation:
        languages:
        - en
        - es
  splits:
  - name: train
    num_bytes: 8241615138
    num_examples: 25227004
  download_size: 3986062875
  dataset_size: 8241615138
- config_name: en-fr
  features:
  - name: translation
    dtype:
      translation:
        languages:
        - en
        - fr
  splits:
  - name: train
    num_bytes: 9718498495
    num_examples: 30340652
  download_size: 4580188433
  dataset_size: 9718498495
- config_name: en-ru
  features:
  - name: translation
    dtype:
      translation:
        languages:
        - en
        - ru
  splits:
  - name: train
    num_bytes: 11156144547
    num_examples: 25173398
  download_size: 4899993315
  dataset_size: 11156144547
- config_name: en-zh
  features:
  - name: translation
    dtype:
      translation:
        languages:
        - en
        - zh
  splits:
  - name: train
    num_bytes: 4988798590
    num_examples: 17451549
  download_size: 2554362693
  dataset_size: 4988798590
- config_name: es-fr
  features:
  - name: translation
    dtype:
      translation:
        languages:
        - es
        - fr
  splits:
  - name: train
    num_bytes: 9230870495
    num_examples: 25887160
  download_size: 4379207947
  dataset_size: 9230870495
- config_name: es-ru
  features:
  - name: translation
    dtype:
      translation:
        languages:
        - es
        - ru
  splits:
  - name: train
    num_bytes: 10789762294
    num_examples: 22294106
  download_size: 4748706797
  dataset_size: 10789762294
- config_name: es-zh
  features:
  - name: translation
    dtype:
      translation:
        languages:
        - es
        - zh
  splits:
  - name: train
    num_bytes: 5475351906
    num_examples: 17599223
  download_size: 2774470102
  dataset_size: 5475351906
- config_name: fr-ru
  features:
  - name: translation
    dtype:
      translation:
        languages:
        - fr
        - ru
  splits:
  - name: train
    num_bytes: 12099649535
    num_examples: 25219973
  download_size: 5264326148
  dataset_size: 12099649535
- config_name: fr-zh
  features:
  - name: translation
    dtype:
      translation:
        languages:
        - fr
        - zh
  splits:
  - name: train
    num_bytes: 5679208110
    num_examples: 17521170
  download_size: 2828146104
  dataset_size: 5679208110
- config_name: ru-zh
  features:
  - name: translation
    dtype:
      translation:
        languages:
        - ru
        - zh
  splits:
  - name: train
    num_bytes: 7905429097
    num_examples: 17920922
  download_size: 3601589709
  dataset_size: 7905429097
configs:
- config_name: ar-en
  data_files:
  - split: train
    path: ar-en/train-*
- config_name: ar-es
  data_files:
  - split: train
    path: ar-es/train-*
- config_name: ar-fr
  data_files:
  - split: train
    path: ar-fr/train-*
- config_name: ar-ru
  data_files:
  - split: train
    path: ar-ru/train-*
- config_name: ar-zh
  data_files:
  - split: train
    path: ar-zh/train-*
- config_name: en-es
  data_files:
  - split: train
    path: en-es/train-*
- config_name: en-fr
  data_files:
  - split: train
    path: en-fr/train-*
- config_name: en-ru
  data_files:
  - split: train
    path: en-ru/train-*
- config_name: en-zh
  data_files:
  - split: train
    path: en-zh/train-*
- config_name: es-fr
  data_files:
  - split: train
    path: es-fr/train-*
- config_name: es-ru
  data_files:
  - split: train
    path: es-ru/train-*
- config_name: es-zh
  data_files:
  - split: train
    path: es-zh/train-*
- config_name: fr-ru
  data_files:
  - split: train
    path: fr-ru/train-*
- config_name: fr-zh
  data_files:
  - split: train
    path: fr-zh/train-*
- config_name: ru-zh
  data_files:
  - split: train
    path: ru-zh/train-*
---

# Dataset Card for United Nations Parallel Corpus

## 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)
  - [Annotations](#annotations)
  - [Personal and Sensitive Information](#personal-and-sensitive-information)
- [Considerations for Using the Data](#considerations-for-using-the-data)
  - [Social Impact of Dataset](#social-impact-of-dataset)
  - [Discussion of Biases](#discussion-of-biases)
  - [Other Known Limitations](#other-known-limitations)
- [Additional Information](#additional-information)
  - [Dataset Curators](#dataset-curators)
  - [Licensing Information](#licensing-information)
  - [Citation Information](#citation-information)
  - [Contributions](#contributions)

## Dataset Description

- **Homepage:** https://opus.nlpl.eu/UNPC/corpus/version/UNPC
- **Repository:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- **Paper:** https://aclanthology.org/L16-1561/
- **Leaderboard:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)
- **Point of Contact:** [More Information Needed](https://github.com/huggingface/datasets/blob/master/CONTRIBUTING.md#how-to-contribute-to-the-dataset-cards)

### Dataset Summary

The United Nations Parallel Corpus is the first parallel corpus composed from United Nations documents published by the original data creator. 
The parallel corpus consists of manually translated UN documents from the last 25 years (1990 to 2014)
for the six official UN languages, Arabic, Chinese, English, French, Russian, and Spanish.
The corpus is freely available for download under a liberal license. 

### Supported Tasks and Leaderboards

The underlying task is machine translation.

### Languages

The six official UN languages: Arabic, Chinese, English, French, Russian, and Spanish.

## Dataset Structure

### Data Instances

[More Information Needed]

### Data Fields

[More Information Needed]

### Data Splits

[More Information Needed]

## 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?

[More Information Needed]

### 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

https://conferences.unite.un.org/UNCORPUS/#disclaimer

The following disclaimer, an integral part of the United Nations Parallel Corpus, shall be respected with regard to the Corpus (no other restrictions apply):
- The United Nations Parallel Corpus is made available without warranty of any kind, explicit or implied. The United Nations specifically makes no warranties or representations as to the accuracy or completeness of the information contained in the United Nations Corpus.
- Under no circumstances shall the United Nations be liable for any loss, liability, injury or damage incurred or suffered that is claimed to have resulted from the use of the United Nations Corpus. The use of the United Nations Corpus is at the user's sole risk. The user specifically acknowledges and agrees that the United Nations is not liable for the conduct of any user. If the user is dissatisfied with any of the material provided in the United Nations Corpus, the user's sole and exclusive remedy is to discontinue using the United Nations Corpus.
- When using the United Nations Corpus, the user must acknowledge the United Nations as the source of the information. For references, please cite this reference: Ziemski, M., Junczys-Dowmunt, M., and Pouliquen, B., (2016), The United Nations Parallel Corpus, Language Resources and Evaluation (LREC’16), Portorož, Slovenia, May 2016.
- Nothing herein shall constitute or be considered to be a limitation upon or waiver, express or implied, of the privileges and immunities of the United Nations, which are specifically reserved.

### Citation Information

```
@inproceedings{ziemski-etal-2016-united,
    title = "The {U}nited {N}ations Parallel Corpus v1.0",
    author = "Ziemski, Micha{\\l}  and
      Junczys-Dowmunt, Marcin  and
      Pouliquen, Bruno",
    booktitle = "Proceedings of the Tenth International Conference on Language Resources and Evaluation ({LREC}'16)",
    month = may,
    year = "2016",
    address = "Portoro{\v{z}}, Slovenia",
    publisher = "European Language Resources Association (ELRA)",
    url = "https://www.aclweb.org/anthology/L16-1561",
    pages = "3530--3534",
    abstract = "This paper describes the creation process and statistics of the official United Nations Parallel Corpus, the first parallel corpus composed from United Nations documents published by the original data creator. The parallel corpus presented consists of manually translated UN documents from the last 25 years (1990 to 2014) for the six official UN languages, Arabic, Chinese, English, French, Russian, and Spanish. The corpus is freely available for download under a liberal license. Apart from the pairwise aligned documents, a fully aligned subcorpus for the six official UN languages is distributed. We provide baseline BLEU scores of our Moses-based SMT systems trained with the full data of language pairs involving English and for all possible translation directions of the six-way subcorpus.",
}
```
### Contributions

Thanks to [@patil-suraj](https://github.com/patil-suraj) for adding this dataset.