| # Dataset Card for allenai/wmt22_african | |
| ## Table of Contents | |
| - [Dataset Description](#dataset-description) | |
| - [Dataset Summary](#dataset-summary) | |
| - [Supported Tasks](#supported-tasks-and-leaderboards) | |
| - [Languages](#languages) | |
| - [Dataset Structure](#dataset-structure) | |
| - [Data Instances](#data-instances) | |
| - [Data Fields](#data-instances) | |
| - [Data Splits](#data-instances) | |
| - [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) | |
| ## Dataset Description | |
| - **Homepage:** https://www.statmt.org/wmt22/large-scale-multilingual-translation-task.html | |
| - **Repository:** [Needs More Information] | |
| - **Paper:** [Needs More Information] | |
| - **Leaderboard:** [Needs More Information] | |
| - **Point of Contact:** [Needs More Information] | |
| ### Dataset Summary | |
| This dataset was created based on [metadata](https://github.com/facebookresearch/LASER/tree/main/data/wmt22_african) for mined bitext released by Meta AI. It contains bitext for 248 pairs for the African languages that are part of the [2022 WMT Shared Task on Large Scale Machine Translation Evaluation for African Languages](https://www.statmt.org/wmt22/large-scale-multilingual-translation-task.html). | |
| #### How to use the data | |
| There are two ways to access the data: | |
| * Via the Hugging Face Python datasets library | |
| ``` | |
| from datasets import load_dataset | |
| dataset = load_dataset("allenai/wmt22_african") | |
| ``` | |
| * Clone the git repo | |
| ``` | |
| git lfs install | |
| git clone https://huggingface.co/datasets/allenai/wmt22_african | |
| ``` | |
| ### Supported Tasks and Leaderboards | |
| This dataset is one of resources allowed under the Constrained Track for the [2022 WMT Shared Task on Large Scale Machine Translation Evaluation for African Languages](https://www.statmt.org/wmt22/large-scale-multilingual-translation-task.html). | |
| ### Languages | |
| #### Focus languages | |
| | Language | Code | | |
| | -------- | ---- | | |
| | Afrikaans | afr | | |
| | Amharic | amh | | |
| | Chichewa | nya | | |
| | Nigerian Fulfulde | fuv | | |
| | Hausa | hau | | |
| | Igbo | ibo | | |
| | Kamba | kam | | |
| | Kinyarwanda | kin | | |
| | Lingala | lin | | |
| | Luganda | lug | | |
| | Luo | luo | | |
| | Northern Sotho | nso | | |
| | Oroma | orm | | |
| | Shona | sna | | |
| | Somali | som | | |
| | Swahili | swh | | |
| | Swati | ssw | | |
| | Tswana | tsn | | |
| | Umbundu | umb | | |
| | Wolof | wol | | |
| | Xhosa | xho | | |
| | Xitsonga | tso | | |
| | Yoruba | yor | | |
| | Zulu | zul | | |
| Colonial linguae francae: English - eng, French - fra | |
| ## Dataset Structure | |
| The dataset contains gzipped tab delimited text files for each direction. Each text file contains lines with parallel sentences. | |
| ### Data Instances | |
| The dataset contains 248 language pairs. | |
| Sentence counts for each pair can be found [here](https://huggingface.co/datasets/allenai/wmt22_african/blob/main/sentence_counts.txt). | |
| ### Data Fields | |
| Every instance for a language pair contains the following fields: 'translation' (containing sentence pairs), 'laser_score', 'source_sentence_lid', 'target_sentence_lid', where 'lid' is language classification probability. | |
| Example: | |
| ``` | |
| { | |
| 'translation': | |
| { | |
| 'afr': 'In Mei 2007, in ooreenstemming met die spesifikasies van die Java Gemeenskapproses, het Sun Java tegnologie geherlisensieer onder die GNU General Public License.', | |
| 'eng': 'As of May 2007, in compliance with the specifications of the Java Community Process, Sun relicensed most of its Java technologies under the GNU General Public License.' | |
| }, | |
| 'laser_score': 1.0717015266418457, | |
| 'source_sentence_lid': 0.9996600151062012, | |
| 'target_sentence_lid': 0.9972000122070312 | |
| } | |
| ``` | |
| ### Data Splits | |
| The data is not split into train, dev, and test. | |
| ## Dataset Creation | |
| ### Curation Rationale | |
| Parallel sentences from monolingual data in Common Crawl and ParaCrawl were identified via [Language-Agnostic Sentence Representation (LASER)](https://github.com/facebookresearch/LASER) encoders. | |
| ### Source Data | |
| #### Initial Data Collection and Normalization | |
| Monolingual data was obtained from Common Crawl and ParaCrawl. | |
| #### Who are the source language producers? | |
| Contributors to web text in Common Crawl and ParaCrawl. | |
| ### Annotations | |
| #### Annotation process | |
| The data was not human annotated. The metadata used to create the dataset can be found here: https://github.com/facebookresearch/LASER/tree/main/data/wmt22_african | |
| #### Who are the annotators? | |
| The data was not human annotated. Parallel text from Common Crawl and Para Crawl monolingual data were identified automatically via [LASER](https://github.com/facebookresearch/LASER) encoders. | |
| ### Personal and Sensitive Information | |
| [Needs More Information] | |
| ## Considerations for Using the Data | |
| ### Social Impact of Dataset | |
| This dataset provides data for training machine learning systems for many languages that have low resources available for NLP. | |
| ### Discussion of Biases | |
| Biases in the data have not been studied. | |
| ### Other Known Limitations | |
| [Needs More Information] | |
| ## Additional Information | |
| ### Dataset Curators | |
| [Needs More Information] | |
| ### Licensing Information | |
| The dataset is released under the terms of [ODC-BY](https://opendatacommons.org/licenses/by/1-0/). By using this, you are also bound by the Internet Archive [Terms of Use](https://archive.org/about/terms.php) in respect of the content contained in the dataset. | |
| ### Citation Information | |
| NLLB Team et al, No Language Left Behind: Scaling Human-Centered Machine Translation, Arxiv, 2022. | |
| ### Contributions | |
| We thank the AllenNLP team at AI2 for hosting and releasing this data, including [Akshita Bhagia](https://akshitab.github.io/) (for engineering efforts to create the huggingface dataset), and [Jesse Dodge](https://jessedodge.github.io/) (for organizing the connection). | |