task_categories:text2text-generation size_categories:10M<n<100M language:pl region:us
---
task_categories:
- text2text-generation
language:
- pl
size_categories:
- 10M<n<100M
---

# PolEval 2022 Task 2 Pretraining Dataset

## Dataset Description

* **Repository:** <https://github.com/Carbon225/poleval-2022-abbr>
* **Paper:** TODO

### Dataset Summary

Abbreviation disambiguation is the process of expanding abbreviations, e.g. "eng." to the full form "engineer".
In the Polish language the task is further complicated because of the many ways to create abbreviations and additional inflected forms.
Abbreviation disambiguation was the topic of the 2022 PolEval Competition Task 2.
This is the dataset used for pretraining in Jakub Karbowski's competition submission.

### Supported Tasks

The dataset contains data suitable for:

* corrupted text restoration
* base/inflected form prediction
* abbreviation disambiguation*

*the abbreviations are not guaranteed to be gramatically correct

### Languages

* Polish

## Dataset Structure

### Fields

* `text` -- a context of 140 to 200 characters where an abbreviation has been used
* `labels` -- the inflected and base forms of the expanded abbreviation

### Format

The abbreviation in `text` is surrounded with `<mask>` `</mask>`.
The `labels` format is `inflected form; base form`.

### Example

text              | labels
------------------|-----------
`jest zgodny ze światem, w którym istnieje problem zła i cierpienie, a <mask>bs.</mask> miłość jest ukryta przed wieloma osobami. Podobną argumentację` | `boska; boski`

## 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

### Licensing Information

[More Information Needed]

### Citation Information

[More Information Needed]