nlptoolkit-datagenerator v1.0.1

Data Generator

Video Lectures

For Developers

You can also see Cython, Java, Python, C++, Swift, or C# repository.

Requirements

• Node.js 14 or higher
• Git

Node.js

To check if you have a compatible version of Node.js installed, use the following command:

node -v

You can find the latest version of Node.js here.

Git

Install the latest version of Git.

Npm Install

npm install nlptoolkit-datagenerator

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-js.git

Open project with Webstorm IDE

Steps for opening the cloned project:

• Start IDE
• Select File | Open from main menu
• Choose DataGenerator-Js file
• Select open as project option
• Couple of seconds, dependencies will be downloaded.

Detailed Description

• AnnotatedDataSetGenerator
• InstanceGenerator

AnnotatedDataSetGenerator

DataSet yaratmak için AnnotatedDataSetGenerator sınıfı önce üretilir.

AnnotatedDataSetGenerator(folder: string, pattern: string, instanceGenerator: InstanceGenerator)

Ardından generate metodu ile DataSet yaratılır.

generate(): DataSet

InstanceGenerator

DataGeneratorlerin InstanceGeneratorlere ihtiyacı vardır. Bunlar bir tek kelimeden bir Instance yaratan sınıflardır.

generateInstanceFromSentence(sentence: Sentence, wordIndex: number): 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

Example Generated DataSet

Word Sense Disambiguation Task

The following Table shows the sample text represented with sense labels and three possible features, namely the root form of the word, the part of speech (POS) tag of the word, and a boolean feature for checking the capital case.

Named Entity Recognition Task

The following Table shows the sample text represented with tag labels and three possible features, namely the root form of the word, the part of speech (POS) tag of the word, and a boolean feature for checking the capital case.

Shallow Parse Task

The following Table shows the sample text represented with chunk labels and three possible features, namely the root form of the word, the part of speech (POS) tag of the word, and a boolean feature for checking the capital case.

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}
}