Create README.md

README.md

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+---
+annotations_creators:
+- found
+- machine-generated
+language:
+- myv
+- ru
+language_creators:
+- found
+- machine-generated
+license:
+- cc-by-sa-4.0
+multilinguality:
+- translation
+pretty_name: Erzya-Russian parallel corpus
+size_categories:
+- 10K<n<100K
+source_datasets:
+- original
+tags:
+- erzya
+- mordovian
+task_categories:
+- translation
+task_ids: []
+---
+
+# Dataset Card for **slone/myv_ru_2022**
+
+## Dataset Description
+
+- **Homepage:**
+- **Repository:**
+- **Paper:**
+- **Leaderboard:**
+- **Point of Contact:**
+
+### Dataset Summary
+
+This is a corpus of parallel Erzya-Russian words, phrases and sentences, collected in the paper "The first neural machine translation system for the Erzya language".
+
+The corpus consists of the following parts:
+
+| name | size | composition | 
+| -----| ---- | -------|
+|train | 74503 | parallel words, phrases and sentences, mined from dictionaries, books and web texts | 
+| dev  | 1500  | parallel sentences mined from books and web texts | 
+| test | 1500  | parallel sentences mined from books and web texts | 
+| mono | 333651| Erzya sentences mined from books and web texts, translated to Russian by a neural model | 
+
+The dev and test splits contain sentences from the following sources
+
+| name | size | description| 
+| ---------------|----| -------|
+|wiki            |600 | Aligned sentences from linked Erzya and Russian Wikipedia articles |
+|bible           |400 | Paired verses from the Bible (https://finugorbib.com) |
+|games           |250 | Aligned sentences from the book *"Сказовые формы мордовской литературы", И.И. Шеянова, 2017, НИИ гуманитарых наук при Правительстве Республики Мордовия, Саранск* |
+|tales           |100 | Aligned sentences from the book *"Мордовские народные игры", В.С. Брыжинский, 2009, Мордовское книжное издательство, Саранск* |
+|fiction         |100 | Aligned sentences from modern Erzya prose and poetry (https://rus4all.ru/myv) |
+|constitution    | 50 | Aligned sentences from the Soviet 1938 constitution |
+
+To load the first three parts (train, validation and test), use the code:
+
+```Python
+from datasets import load_dataset
+data = load_dataset('slone/myv_ru_2022')
+```
+
+To load all four parts (included the back-translated data), please specify the data files explicitly:
+```Python
+from datasets import load_dataset
+data_extended = load_dataset(
+    'slone/myv_ru_2022',
+    data_files={'train':'train.jsonl', 'valiation': 'dev.jsonl', 'test': 'test.jsonl', 'mono': 'back_translated.jsonl'}
+)
+```
+
+### Supported Tasks and Leaderboards
+
+- `translation`: the dataset may be used to train `ru-myv` translation models. There are no specific leaderboards for it yet, but if you feel like discussing it, welcome to the comments!
+
+### Languages
+
+The main part of the dataset (`train`, `dev` and `test`) consists of "natural" Erzya and Russian sentences, translated to the other language by humans. There is also a larger Erzya-only part of the corpus (`mono`), translated to Russian automatically.
+
+## Dataset Structure
+
+### Data Instances
+
+All data instances have three string fields: `myv`, `ru` and `src` (the last one is currently meaningful only for dev and test splits), for example:
+```
+{'myv': 'Сюкпря Пазонтень, кие кирвазтизе Титэнь седейс тынк кисэ секе жо бажамонть, кона палы минек седейсэяк!',
+ 'ru': 'Благодарение Богу, вложившему в сердце Титово такое усердие к вам.',
+ 'src': 'bible'}
+```
+
+### Data Fields
+
+- `myv`: the Erzya text (word, phrase, or sentence)
+- `ru`: the corresponding Russian text
+- `src`: the source of data (only for dev and test splits)
+
+### 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?
+
+No human annotation was involved in data collection.
+
+### Personal and Sensitive Information
+
+All data was collected from public sources, so no sensitive information is expected in them. 
+However, some sentences collected, for example, from news articles or LiveJournal posts, can contain personal data.
+
+## Considerations for Using the Data
+
+### Social Impact of Dataset
+
+[More Information Needed]
+
+### Discussion of Biases
+
+Most of the dataset has been collected by automatical means, so it may contain errors and noise. 
+Some types of these errors are systemic: for example, the words for "Erzya" and "Russian" are often aligned together, 
+because they appear in the corresponding Wikipedias on similar positions.
+
+### Other Known Limitations
+
+[More Information Needed]
+
+## Additional Information
+
+### Dataset Curators
+
+[More Information Needed]
+
+### Licensing Information
+
+[More Information Needed]
+
+### Citation Information
+
+[More Information Needed]