Metadata-Version: 2.1
Name: NlpToolkit-DataGenerator-Cy
Version: 1.0.1
Summary: Classification dataset generator library for high level Nlp tasks
Home-page: https://github.com/StarlangSoftware/DataGenerator-Cy
Author: olcaytaner
Author-email: olcay.yildiz@ozyegin.edu.tr
License: UNKNOWN
Description: For Developers
        ============
        You can also see [Python](https://github.com/starlangsoftware/DataGenerator-Py), [Java](https://github.com/starlangsoftware/DataGenerator), [C++](https://github.com/starlangsoftware/DataGenerator-CPP),  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}
        }
        
Platform: UNKNOWN
Description-Content-Type: text/markdown
