Metadata-Version: 2.1
Name: anncorra
Version: 0.0.3
Summary: Anncorra is a python package for giving meaning to POS (Part of Speech) tags.
Home-page: https://github.com/kuldip-barot/anncorra
Author: Kuldeep Barot
License: Apache License 2.0
Description: # Tags of AnnCorra 
        
        [![GitHub issues](https://img.shields.io/github/issues/kuldip-barot/anncorra)](https://github.com/kuldip-barot/anncorra/issues) [![GitHub forks](https://img.shields.io/github/forks/kuldip-barot/anncorra)](https://github.com/kuldip-barot/anncorra/network) [![GitHub stars](https://img.shields.io/github/stars/kuldip-barot/anncorra)](https://github.com/kuldip-barot/anncorra/stargazers) ![GitHub](https://img.shields.io/github/license/kuldip-barot/anncorra)  
        Indian Language Machine Translation (ILMT) project has taken the task of annotating corpora **(AnnCorra)** of several Indian languages and came up with tags which have been defined for the tagging schemes for POS (part of speech) tagging.
        
        This repository would explain the [POS](https://en.wikipedia.org/wiki/Part-of-speech_tagging) (Part Of Speech) Tags along with examples.
        
        ## Requirements
        
        Package requires the following to run:
        
          * [python](https://www.python.org/downloads/) (preferable version 3+)
        
        
        ## Installation
        
        Use the package manager [pip](https://pip.pypa.io/en/stable/) to install foobar.
        
        ```bash
        pip install anncorra
        ``` 
        
        or
        
        ```bash
        git clone https://github.com/kuldip-barot/anncorra.git
        cd anncorra
        python setup.py install
        ``` 
        
        ## Usage
        
        Import the package after installation.
        
        ```python
        >>> import anncorra
        >>> anncorra.explain('NN')
        ```
        The output of above command:
        
            POS Tags :  NN
            Full form :  Noun
            Desription :  The tag NN tag set makes a distinction between noun singular (NN) and noun plural (NNS).
            Example :
            yaha bAta  galI_NN galI_RDP meM  phEla gayI
             'this' 'talk'  'lane'      'lane'         'in'    'spread' 'went'
             “The word was spread in every lane”.
         
        
        ## Contributing
        
        Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
        
        ## References
        
        [AnnCorra : Annotating Corpora; Guidelines For POS And Chunk Annotation For Indian Languages](http://ltrc.iiit.ac.in/winterschool08/content/data/revised-chunk-pos-ann-guidelines-15-Dec-06.doc)
        
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: License :: OSI Approved :: Apache Software License
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3.5
Classifier: Programming Language :: Python :: 3.6
Classifier: Topic :: Software Development :: Libraries
Classifier: Topic :: Software Development :: Libraries :: Python Modules
Classifier: Intended Audience :: Developers
Requires-Python: >=3.5
Description-Content-Type: text/markdown
