Classification dataset generator library for high level Nlp tasks
Project description
Data Generator ============
Video Lectures
============
[<img src=https://github.com/StarlangSoftware/DataGenerator/blob/master/video1.jpg width="50%">](https://youtu.be/E9rE_eCffPE)[<img src=https://github.com/StarlangSoftware/DataGenerator/blob/master/video2.jpg width="50%">](https://youtu.be/ISHmGWvHL7k)
For Developers
============
You can also see [Python](https://github.com/starlangsoftware/DataGenerator-Py), [Java](https://github.com/starlangsoftware/DataGenerator), [Js](https://github.com/starlangsoftware/DataGenerator-Js), [C++](https://github.com/starlangsoftware/DataGenerator-CPP), [C](https://github.com/starlangsoftware/DataGenerator-C), [Swift](https://github.com/starlangsoftware/DataGenerator-Swift), or [C#](https://github.com/starlangsoftware/DataGenerator-CS) repository.
## Requirements
* [Python 3.7 or higher](#python)
* [Git](#git)
### Python
To check if you have a compatible version of Python installed, use the following command:
python -V
You can find the latest version of Python [here](https://www.python.org/downloads/).
### Git
Install the [latest version of Git](https://git-scm.com/book/en/v2/Getting-Started-Installing-Git).
## Pip Install
pip3 install NlpToolkit-DataGenerator-Cy
## Download Code
In order to work on code, create a fork from GitHub page.
Use Git for cloning the code to your local or below line for Ubuntu:
git clone <your-fork-git-link>
A directory called DataGenerator will be created. Or you can use below link for exploring the code:
git clone https://github.com/starlangsoftware/DataGenerator-Cy.git
## Open project with Pycharm IDE
Steps for opening the cloned project:
* Start IDE
* Select **File | Open** from main menu
* Choose `DataGenerator-CY` file
* Select open as project option
* Couple of seconds, dependencies will be downloaded.
Detailed Description
============
+ [AnnotatedDataSetGenerator](#annotateddatasetgenerator)
+ [InstanceGenerator](#instancegenerator)
## AnnotatedDataSetGenerator
DataSet yaratmak için AnnotatedDataSetGenerator sınıfı önce üretilir.
AnnotatedDataSetGenerator(self, folder: str, pattern: str, instanceGenerator: InstanceGenerator)
Ardından generate metodu ile DataSet yaratılır.
generate(self) -> DataSet
## InstanceGenerator
DataGeneratorlerin InstanceGeneratorlere ihtiyacı vardır. Bunlar bir tek kelimeden bir
Instance yaratan sınıflardır.
generateInstanceFromSentence(self, sentence: Sentence, wordIndex: int) -> Instance
NER problemi için NerInstanceGenerator, FeaturedNerInstanceGenerator ve
VectorizedNerInstanceGeneratorsınıfı
ShallowParse problemi için ShallowParseInstanceGenerator,
FeaturedShallowParseInstanceGenerator ve VectorizedShallowParseInstanceGenerator sınıfı
WSD problemi için SemanticInstanceGenerator, FeaturedSemanticInstanceGenerator ve
VectorizedSemanticInstanceGenerator sınıfı
Morphological Disambiguation problemi için FeaturedDisambiguationInstanceGenerator sınıfı
## Cite
If you use this resource on your research, please cite the following paper:
```
@article{acikgoz,
title={All-words word sense disambiguation for {T}urkish},
author={O. Açıkg{\"o}z and A. T. G{\"u}rkan and B. Ertopçu and O. Topsakal and B. {\"O}zenç and A. B. Kanburoğlu and {\.{I}}. Çam and B. Avar and G. Ercan and O. T. Y{\i}ld{\i}z},
journal={2017 International Conference on Computer Science and Engineering (UBMK)},
year={2017},
pages={490-495}
}
@inproceedings{ertopcu17,
author={B. {Ertopçu} and A. B. {Kanburoğlu} and O. {Topsakal} and O. {Açıkgöz} and A. T. {Gürkan} and B. {Özenç} and İ. {Çam} and B. {Avar} and G. {Ercan} and O. T. {Yıldız}},
booktitle={2017 International Conference on Computer Science and Engineering (UBMK)}, title={A new approach for named entity recognition},
year={2017},
pages={474-479}
}
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