ua-gec 1.1.1

UA-GEC: Grammatical Error Correction and Fluency Corpus for the Ukrainian language

UA-GEC: Grammatical Error Correction and Fluency Corpus for the Ukrainian Language

This package contains the UA-GEC data and code to work with it.

Python library

There is a Python package that consists of the data and the code to work with it.

Getting started

A simple way to install the package is by pip:

    $ pip install ua_gec==1.1

Alternatively, you can install it from source:

    $ cd python
    $ python setup.py develop

Iterating through corpus

Once installed, you may get annotated documents from Python code:

    >>> from ua_gec import Corpus
    >>> corpus = Corpus(partition="train")
    >>> for doc in corpus:
    ...     print(doc.source)
    ...     print(doc.target)
    ...     print(doc.annotated)
    ...     print(doc.meta.region)

Working with annotations

[The docs are under construction]

Train-test split

We expect users of the corpus train and tune their models on the train split only (of course, you are free to further split it into train-dev or use cross-validation). Use the test split for reporting scores of your final models. Never optimize on the test set. Do not tune hyperparameters on it. And please, do not use it for model selection in any way.

The Statistics for the per-split statistics.

Annotation format

Annotated files are text file that use the following in-text annotation format: {error=>edit:::error_type=Tag}, where error and edit stand for the text item before and after correction, respectively, and Tag denotes an error category (Grammar, Spelling, Punctuation, or Fluency).

Example of an annotated text:

    I {like=>likes:::error_type=Grammar} turtles.

An accompanying Python package, ua_gec, provides many tools for working with annotated texts. See its documentation for details.

Statistics

UA-GEC contains:

Split	Documents	Sentences	Tokens	Authors
train	851	18,225	285,247	416
test	160	2,490	43,432	76
TOTAL	1,011	20,715	328,779	492

The corpus statistics can be generated by running a script from the Python package (note that the ua-gec package must be installed first):

$ python ./python/ua_gec/stats.py

Contributing

• The data collection is an ongoing activity. You can always contribute your Ukrainian writings or complete one of the writing tasks at https://ua-gec-dataset.grammarly.ai/

• Code and documentation improvements are welcomed. Please, open a pull request.

Contacts

• [e-mail]