
# Ukrainian Wikipedia Edits

### Dataset summary

A collection of over 5M sentence edits extracted from Ukrainian Wikipedia history revisions.

Edits were filtered by edit distance and sentence length. This makes them usable for grammatical error correction (GEC) or spellchecker models pre-training.


### Supported Tasks and Leaderboards

* Ukrainian grammatical error correction (GEC) - see [UA-GEC](https://github.com/grammarly/ua-gec)
* Ukrainian spelling correction

### Languages

Ukrainian

## Dataset Structure

### Data Fields

* `src` - sentence before edit
* `tgt` - sentence after edit

### Data Splits

* `full/train` contains all the data (5,243,376 samples)
* `tiny/train` contains a 5000 examples sample.

## Dataset Creation

Latest full Ukrainian Wiki dump were used as of 2022-04-30.

It was processed with the [wikiedits](https://github.com/snukky/wikiedits) and custom scripts.

### Source Data

#### Initial Data Collection and Normalization

Wikipedia

#### Who are the source language producers?

Wikipedia writers

### Annotations

#### Annotation process

Annotations inferred by comparing two subsequent page revisions.

#### Who are the annotators?

People who edit Wikipedia pages.

### Personal and Sensitive Information

No

## Considerations for Using the Data

### Social Impact of Dataset

[More Information Needed]

### Discussion of Biases

[More Information Needed]

### Other Known Limitations

The data is noisy. In addition to GEC and spelling edits, it contains a good chunk of factual changes and vandalism.

More task-specific filters could help.

## Additional Information

### Dataset Curators

[Oleksiy Syvokon](https://github.com/asivokon)

### Licensing Information

CC-BY-3.0

### Citation Information

```
@inproceedings{wiked2014,
    author = {Roman Grundkiewicz and Marcin Junczys-Dowmunt},
    title = {The WikEd Error Corpus: A Corpus of Corrective Wikipedia Edits and its Application to Grammatical Error Correction},
    booktitle = {Advances in Natural Language Processing -- Lecture Notes in Computer Science},
    editor = {Adam Przepiórkowski and Maciej Ogrodniczuk},
    publisher = {Springer},
    year = {2014},
    volume = {8686},
    pages = {478--490},
    url = {http://emjotde.github.io/publications/pdf/mjd.poltal2014.draft.pdf}
}
```

### Contributions

[@snukky](https://github.com/snukky) created tools for dataset processing.

[@asivokon](https://github.com/asivokon) generated this dataset.

task_categories:other annotations_creators:crowdsourced language_creators:crowdsourced multilinguality:monolingual multilinguality:translation size_categories:1M<n<10M source_datasets:original license:cc-by-3.0 region:us
{"annotations_creators": ["crowdsourced"], "language_creators": ["crowdsourced"], "language": ["uk-UA"], "license": ["cc-by-3.0"], "multilinguality": ["monolingual", "translation"], "size_categories": ["1M<n<10M"], "source_datasets": ["original"], "task_categories": ["other"], "task_ids": [], "pretty_name": "Ukrainian Wikipedia edits "}
TAGS
#task_categories-other #annotations_creators-crowdsourced #language_creators-crowdsourced #multilinguality-monolingual #multilinguality-translation #size_categories-1M<n<10M #source_datasets-original #license-cc-by-3.0 #region-us 


# Ukrainian Wikipedia Edits

### Dataset summary

A collection of over 5M sentence edits extracted from Ukrainian Wikipedia history revisions.

Edits were filtered by edit distance and sentence length. This makes them usable for grammatical error correction (GEC) or spellchecker models pre-training.


### Supported Tasks and Leaderboards

* Ukrainian grammatical error correction (GEC) - see UA-GEC
* Ukrainian spelling correction

### Languages

Ukrainian

## Dataset Structure

### Data Fields

* 'src' - sentence before edit
* 'tgt' - sentence after edit

### Data Splits

* 'full/train' contains all the data (5,243,376 samples)
* 'tiny/train' contains a 5000 examples sample.

## Dataset Creation

Latest full Ukrainian Wiki dump were used as of 2022-04-30.

It was processed with the wikiedits and custom scripts.

### Source Data

#### Initial Data Collection and Normalization

Wikipedia

#### Who are the source language producers?

Wikipedia writers

### Annotations

#### Annotation process

Annotations inferred by comparing two subsequent page revisions.

#### Who are the annotators?

People who edit Wikipedia pages.

### Personal and Sensitive Information

No

## Considerations for Using the Data

### Social Impact of Dataset



### Discussion of Biases



### Other Known Limitations

The data is noisy. In addition to GEC and spelling edits, it contains a good chunk of factual changes and vandalism.

More task-specific filters could help.

## Additional Information

### Dataset Curators

Oleksiy Syvokon

### Licensing Information

CC-BY-3.0





### Contributions

@snukky created tools for dataset processing.

@asivokon generated this dataset.

# Ukrainian Wikipedia Edits ### Dataset summary

A collection of over 5M sentence edits extracted from Ukrainian Wikipedia history revisions.

Edits were filtered by edit distance and sentence length. This makes them usable for grammatical error correction (GEC) or spellchecker models pre-training. ### Supported Tasks and Leaderboards

* Ukrainian grammatical error correction (GEC) - see UA-GEC
* Ukrainian spelling correction ### Languages

Ukrainian ## Dataset Structure ### Data Fields

* 'src' - sentence before edit
* 'tgt' - sentence after edit ### Data Splits

* 'full/train' contains all the data (5,243,376 samples)
* 'tiny/train' contains a 5000 examples sample. ## Dataset Creation

Latest full Ukrainian Wiki dump were used as of 2022-04-30.

It was processed with the wikiedits and custom scripts. ### Source Data #### Initial Data Collection and Normalization

Wikipedia #### Who are the source language producers?

Wikipedia writers ### Annotations #### Annotation process

Annotations inferred by comparing two subsequent page revisions. #### Who are the annotators?

People who edit Wikipedia pages. ### Personal and Sensitive Information

No ## Considerations for Using the Data ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations

The data is noisy. In addition to GEC and spelling edits, it contains a good chunk of factual changes and vandalism.

More task-specific filters could help. ## Additional Information ### Dataset Curators

Oleksiy Syvokon ### Licensing Information

CC-BY-3.0 ### Contributions

@snukky created tools for dataset processing.

@asivokon generated this dataset.
TAGS
#task_categories-other #annotations_creators-crowdsourced #language_creators-crowdsourced #multilinguality-monolingual #multilinguality-translation #size_categories-1M<n<10M #source_datasets-original #license-cc-by-3.0 #region-us 
 # Ukrainian Wikipedia Edits ### Dataset summary

A collection of over 5M sentence edits extracted from Ukrainian Wikipedia history revisions.

Edits were filtered by edit distance and sentence length. This makes them usable for grammatical error correction (GEC) or spellchecker models pre-training. ### Supported Tasks and Leaderboards

* Ukrainian grammatical error correction (GEC) - see UA-GEC
* Ukrainian spelling correction ### Languages

Ukrainian ## Dataset Structure ### Data Fields

* 'src' - sentence before edit
* 'tgt' - sentence after edit ### Data Splits

* 'full/train' contains all the data (5,243,376 samples)
* 'tiny/train' contains a 5000 examples sample. ## Dataset Creation

Latest full Ukrainian Wiki dump were used as of 2022-04-30.

It was processed with the wikiedits and custom scripts. ### Source Data #### Initial Data Collection and Normalization

Wikipedia #### Who are the source language producers?

Wikipedia writers ### Annotations #### Annotation process

Annotations inferred by comparing two subsequent page revisions. #### Who are the annotators?

People who edit Wikipedia pages. ### Personal and Sensitive Information

No ## Considerations for Using the Data ### Social Impact of Dataset ### Discussion of Biases ### Other Known Limitations

The data is noisy. In addition to GEC and spelling edits, it contains a good chunk of factual changes and vandalism.

More task-specific filters could help. ## Additional Information ### Dataset Curators

Oleksiy Syvokon ### Licensing Information

CC-BY-3.0 ### Contributions

@snukky created tools for dataset processing.

@asivokon generated this dataset.
passage: TAGS
#task_categories-other #annotations_creators-crowdsourced #language_creators-crowdsourced #multilinguality-monolingual #multilinguality-translation #size_categories-1M<n<10M #source_datasets-original #license-cc-by-3.0 #region-us 
# Ukrainian Wikipedia Edits### Dataset summary

A collection of over 5M sentence edits extracted from Ukrainian Wikipedia history revisions.

Edits were filtered by edit distance and sentence length. This makes them usable for grammatical error correction (GEC) or spellchecker models pre-training.### Supported Tasks and Leaderboards

* Ukrainian grammatical error correction (GEC) - see UA-GEC
* Ukrainian spelling correction### Languages

Ukrainian## Dataset Structure### Data Fields

* 'src' - sentence before edit
* 'tgt' - sentence after edit### Data Splits

* 'full/train' contains all the data (5,243,376 samples)
* 'tiny/train' contains a 5000 examples sample.## Dataset Creation

Latest full Ukrainian Wiki dump were used as of 2022-04-30.

It was processed with the wikiedits and custom scripts.### Source Data#### Initial Data Collection and Normalization

Wikipedia#### Who are the source language producers?

Wikipedia writers### Annotations#### Annotation process

Annotations inferred by comparing two subsequent page revisions.#### Who are the annotators?

People who edit Wikipedia pages.### Personal and Sensitive Information

No## Considerations for Using the Data### Social Impact of Dataset### Discussion of Biases### Other Known Limitations

The data is noisy. In addition to GEC and spelling edits, it contains a good chunk of factual changes and vandalism.

More task-specific filters could help.## Additional Information### Dataset Curators

Oleksiy Syvokon### Licensing Information

CC-BY-3.0### Contributions

@snukky created tools for dataset processing.

@asivokon generated this dataset.