
# 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.
task_categories:translation annotations_creators:found language_creators:found multilinguality:multilingual size_categories:10M<n<100M source_datasets:original language:ar language:en language:es language:fr language:ru language:zh license:other region:us
{"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": 8039689939, "num_examples": 20044478}], "download_size": 2025106743, "dataset_size": 8039689939}, {"config_name": "ar-es", "features": [{"name": "translation", "dtype": {"translation": {"languages": ["ar", "es"]}}}], "splits": [{"name": "train", "num_bytes": 8715754848, "num_examples": 20532014}], "download_size": 2167791297, "dataset_size": 8715754848}, {"config_name": "ar-fr", "features": [{"name": "translation", "dtype": {"translation": {"languages": ["ar", "fr"]}}}], "splits": [{"name": "train", "num_bytes": 8897848038, "num_examples": 20281645}], "download_size": 2188765415, "dataset_size": 8897848038}, {"config_name": "ar-ru", "features": [{"name": "translation", "dtype": {"translation": {"languages": ["ar", "ru"]}}}], "splits": [{"name": "train", "num_bytes": 11395923083, "num_examples": 20571334}], "download_size": 2476562835, "dataset_size": 11395923083}, {"config_name": "ar-zh", "features": [{"name": "translation", "dtype": {"translation": {"languages": ["ar", "zh"]}}}], "splits": [{"name": "train", "num_bytes": 6447658008, "num_examples": 17306056}], "download_size": 1738869755, "dataset_size": 6447658008}, {"config_name": "en-es", "features": [{"name": "translation", "dtype": {"translation": {"languages": ["en", "es"]}}}], "splits": [{"name": "train", "num_bytes": 8241635322, "num_examples": 25227004}], "download_size": 2300411698, "dataset_size": 8241635322}, {"config_name": "en-fr", "features": [{"name": "translation", "dtype": {"translation": {"languages": ["en", "fr"]}}}], "splits": [{"name": "train", "num_bytes": 9718522775, "num_examples": 30340652}], "download_size": 2657208676, "dataset_size": 9718522775}, {"config_name": "en-ru", "features": [{"name": "translation", "dtype": {"translation": {"languages": ["en", "ru"]}}}], "splits": [{"name": "train", "num_bytes": 11156164691, "num_examples": 25173398}], "download_size": 2589707636, "dataset_size": 11156164691}, {"config_name": "en-zh", "features": [{"name": "translation", "dtype": {"translation": {"languages": ["en", "zh"]}}}], "splits": [{"name": "train", "num_bytes": 4988812558, "num_examples": 17451549}], "download_size": 1535707641, "dataset_size": 4988812558}, {"config_name": "es-fr", "features": [{"name": "translation", "dtype": {"translation": {"languages": ["es", "fr"]}}}], "splits": [{"name": "train", "num_bytes": 9230891207, "num_examples": 25887160}], "download_size": 2492342915, "dataset_size": 9230891207}, {"config_name": "es-ru", "features": [{"name": "translation", "dtype": {"translation": {"languages": ["es", "ru"]}}}], "splits": [{"name": "train", "num_bytes": 10789780134, "num_examples": 22294106}], "download_size": 2487664520, "dataset_size": 10789780134}, {"config_name": "es-zh", "features": [{"name": "translation", "dtype": {"translation": {"languages": ["es", "zh"]}}}], "splits": [{"name": "train", "num_bytes": 5475365986, "num_examples": 17599223}], "download_size": 1639717723, "dataset_size": 5475365986}, {"config_name": "fr-ru", "features": [{"name": "translation", "dtype": {"translation": {"languages": ["fr", "ru"]}}}], "splits": [{"name": "train", "num_bytes": 12099669711, "num_examples": 25219973}], "download_size": 2762585269, "dataset_size": 12099669711}, {"config_name": "fr-zh", "features": [{"name": "translation", "dtype": {"translation": {"languages": ["fr", "zh"]}}}], "splits": [{"name": "train", "num_bytes": 5679222134, "num_examples": 17521170}], "download_size": 1668823634, "dataset_size": 5679222134}, {"config_name": "ru-zh", "features": [{"name": "translation", "dtype": {"translation": {"languages": ["ru", "zh"]}}}], "splits": [{"name": "train", "num_bytes": 7905443441, "num_examples": 17920922}], "download_size": 1934425373, "dataset_size": 7905443441}]}
TAGS
#task_categories-translation #annotations_creators-found #language_creators-found #multilinguality-multilingual #size_categories-10M<n<100M #source_datasets-original #language-Arabic #language-English #language-Spanish #language-French #language-Russian #language-Chinese #license-other #region-us 


# Dataset Card for United Nations Parallel Corpus

## Table of Contents
- Dataset Description
  - Dataset Summary
  - Supported Tasks and Leaderboards
  - Languages
- Dataset Structure
  - Data Instances
  - Data Fields
  - Data Splits
- Dataset Creation
  - Curation Rationale
  - Source Data
  - Annotations
  - Personal and Sensitive Information
- Considerations for Using the Data
  - Social Impact of Dataset
  - Discussion of Biases
  - Other Known Limitations
- Additional Information
  - Dataset Curators
  - Licensing Information
  - Citation Information
  - Contributions

## Dataset Description

- Homepage: URL
- Repository: 
- Paper: URL
- Leaderboard: 
- Point of Contact: 

### 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



### Data Fields



### Data Splits



## Dataset Creation

### Curation Rationale



### Source Data

#### Initial Data Collection and Normalization



#### Who are the source language producers?



### Annotations

#### Annotation process



#### Who are the annotators?



### Personal and Sensitive Information



## Considerations for Using the Data

### Social Impact of Dataset



### Discussion of Biases



### Other Known Limitations



## Additional Information

### Dataset Curators



### Licensing Information

URL

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.




### Contributions

Thanks to @patil-suraj for adding this dataset.
# Dataset Card for United Nations Parallel Corpus ## Table of Contents
- Dataset Description
  - Dataset Summary
  - Supported Tasks and Leaderboards
  - Languages
- Dataset Structure
  - Data Instances
  - Data Fields
  - Data Splits
- Dataset Creation
  - Curation Rationale
  - Source Data
  - Annotations
  - Personal and Sensitive Information
- Considerations for Using the Data
  - Social Impact of Dataset
  - Discussion of Biases
  - Other Known Limitations
- Additional Information
  - Dataset Curators
  - Licensing Information
  - Citation Information
  - Contributions ## Dataset Description

- Homepage: URL
- Repository: 
- Paper: URL
- Leaderboard: 
- Point of Contact: ### 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 ### Data Fields ### Data Splits ## Dataset Creation ### Curation Rationale ### Source Data #### Initial Data Collection and Normalization #### Who are the source language producers? ### Annotations #### Annotation process #### Who are the annotators? ### Personal and Sensitive Information ## Considerations for Using the Data ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations ## Additional Information ### Dataset Curators ### Licensing Information

URL

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. ### Contributions

Thanks to @patil-suraj for adding this dataset.
TAGS
#task_categories-translation #annotations_creators-found #language_creators-found #multilinguality-multilingual #size_categories-10M<n<100M #source_datasets-original #language-Arabic #language-English #language-Spanish #language-French #language-Russian #language-Chinese #license-other #region-us 
 # Dataset Card for United Nations Parallel Corpus ## Table of Contents
- Dataset Description
  - Dataset Summary
  - Supported Tasks and Leaderboards
  - Languages
- Dataset Structure
  - Data Instances
  - Data Fields
  - Data Splits
- Dataset Creation
  - Curation Rationale
  - Source Data
  - Annotations
  - Personal and Sensitive Information
- Considerations for Using the Data
  - Social Impact of Dataset
  - Discussion of Biases
  - Other Known Limitations
- Additional Information
  - Dataset Curators
  - Licensing Information
  - Citation Information
  - Contributions ## Dataset Description

- Homepage: URL
- Repository: 
- Paper: URL
- Leaderboard: 
- Point of Contact: ### 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 ### Data Fields ### Data Splits ## Dataset Creation ### Curation Rationale ### Source Data #### Initial Data Collection and Normalization #### Who are the source language producers? ### Annotations #### Annotation process #### Who are the annotators? ### Personal and Sensitive Information ## Considerations for Using the Data ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations ## Additional Information ### Dataset Curators ### Licensing Information

URL

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. ### Contributions

Thanks to @patil-suraj for adding this dataset.
passage: TAGS
#task_categories-translation #annotations_creators-found #language_creators-found #multilinguality-multilingual #size_categories-10M<n<100M #source_datasets-original #language-Arabic #language-English #language-Spanish #language-French #language-Russian #language-Chinese #license-other #region-us 
# Dataset Card for United Nations Parallel Corpus## Table of Contents
- Dataset Description
  - Dataset Summary
  - Supported Tasks and Leaderboards
  - Languages
- Dataset Structure
  - Data Instances
  - Data Fields
  - Data Splits
- Dataset Creation
  - Curation Rationale
  - Source Data
  - Annotations
  - Personal and Sensitive Information
- Considerations for Using the Data
  - Social Impact of Dataset
  - Discussion of Biases
  - Other Known Limitations
- Additional Information
  - Dataset Curators
  - Licensing Information
  - Citation Information
  - Contributions## Dataset Description

- Homepage: URL
- Repository: 
- Paper: URL
- Leaderboard: 
- Point of Contact:### 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### Data Fields### Data Splits## Dataset Creation### Curation Rationale### Source Data#### Initial Data Collection and Normalization#### Who are the source language producers?### Annotations#### Annotation process#### Who are the annotators?### Personal and Sensitive Information## Considerations for Using the Data### Social Impact of Dataset### Discussion of Biases### Other Known Limitations## Additional Information### Dataset Curators