Metadata-Version: 1.1
Name: pntl
Version: 0.2.0
Summary: used to interface with Senna and stanford-parser.jar
Home-page: https://github.com/jawahar273/practNLPTools-lite
Author: Jawahar S
Author-email: jawahar273@gmail.com
License: MIT license
Description: ==================
        practNLPTools-lite
        ==================
        Creating practNLPTools in lite mode.[ get the old coding in dev branch ]
        
        |Author|  |Python-version-3|
        
        |Build Status| - on click this built this might take you to build of
        `practNLPTools`_ which is testing ground for this repository so don’t
        worry.
        
        |FOSSA Status|
        
        | Practical Natural Language Processing Tools for Humans.
        | practNLPTools is a pythonic library over `SENNA`_ and Stanford
          Dependency Extractor.
        
        .. image:: https://img.shields.io/pypi/v/practNLPTools-lite.svg
                :target: https://pypi.python.org/pypi/practNLPTools-lite
        
        .. image:: https://img.shields.io/travis/jawahar273/practNLPTools-lite.svg
                :target: https://travis-ci.org/jawahar273/practNLPTools-lite
        
        .. image:: https://readthedocs.org/projects/pntl/badge/?version=latest
                :target: https://practNLPTools-lite.readthedocs.io/en/latest/?badge=latest
                :alt: Documentation Status
        
        .. image:: https://pyup.io/repos/github/jawahar273/practNLPTools-lite/shield.svg
             :target: https://pyup.io/repos/github/jawahar273/practNLPTools-lite/
             :alt: Updates
        
        .. image:: https://pyup.io/repos/github/jawahar273/practNLPTools-lite/python-3-shield.svg
             :target: https://pyup.io/repos/github/jawahar273/practNLPTools-lite/
             :alt: Python 3
        
        * Documentation: http://pntl.readthedocs.io
        
        Functionality
        =============
        
        -  Semantic Role Labeling
        -  Syntactic Parsing
        -  Part of Speech Tagging (POS Tagging)
        -  Named Entity Recognisation (NER)
        -  Dependency Parsing
        -  Shallow Chunking
        -  Skip-gram(in-case)
        
        Future work
        ===========
        
        -  [STRIKEOUT: automatic takes senna path if it install in system]
        -  copying stanford parser and depPaser file into installed direction
        -  creating depParser for corresponding os environment
        -  custome input format for stanford parser insted of tree format
        
        Features
        ========
        
        #. Fast: `SENNA`_ is written is C. So it is Fast.
        #. We use only dependency Extractor Component of Stanford Parser, which
           takes in Syntactic Parse from SENNA and applies dependency
           Extraction. So there is no need to load parsing models for Stanford
           Parser, which takes time.
        #. Easy to use.
        #. Platform Supported - Windows, Linux and Mac
        
        .. note::
            
            SENNA pipeline has a fixed maximum size of the sentences that it
            can read. By default it is 1024 token/sentence. If you have larger
            sentences, changing the MAX\_SENTENCE\_SIZE value in SENNA\_main.c should beconsidered and your system specific binary should be rebuilt. Otherwise this could introduce misalignment errors.
        
        Installation
        ============
        
        | Requires:
        | A computer with 500mb memory, Java Runtime Environment (1.7
          preferably, works with 1.6 too, but didnt test.) installed and python.
        
        | If you are in linux:
        | run:
        
        ::
        
            sudo python setup.py install 
        
        | If you are in windows:
        | run this commands as administrator:
        
        ::
        
            python setup.py install
        
        
        Bench Mark comparsion
        =====================
        
        By using the ``time`` command in ubuntu on running the ``testsrl.py`` on
        this `link`_ and along with ``tools.py`` on ``pntl``
        
        .. _link: https://github.com/jawahar273/SRLTagger
        
        
        +-----------------+-----------------+-----------------+
        |                 | pntl            | NLTK-senna      |
        +=================+=================+=================+
        | at fist run     |                 |                 |
        +-----------------+-----------------+-----------------+
        |                 | real 0m1.674s   | real 0m2.484s   |
        +-----------------+-----------------+-----------------+
        |                 | user 0m1.564s   | user 0m1.868s   |
        +-----------------+-----------------+-----------------+
        |                 | sys 0m0.228s    | sys 0m0.524s    |
        +-----------------+-----------------+-----------------+
        | at second run   |                 |                 |
        +-----------------+-----------------+-----------------+
        |                 | real 0m1.245s   | real 0m3.359s   |
        +-----------------+-----------------+-----------------+
        |                 | user 0m1.560s   | user 0m2.016s   |
        +-----------------+-----------------+-----------------+
        |                 | sys 0m0.152s    | sys 0m1.168s    |
        +-----------------+-----------------+-----------------+
        
        
        .. raw:: html
        
           <div>
        
        note: this bench mark may differt accouding to system’s working and to
        restult present here is exact same result in my system ububtu 4Gb RAM
        and i3 process. If I find another good benchmark techinque then I will
        change to it.
        
        .. raw:: html
        
           </div>
        
        .. _practNLPTools: https://github.com/jawahar273/practNLPTools-lite
        .. _SENNA: http://ronan.collobert.com/senna/
        
        .. |Author| image:: https://img.shields.io/badge/Author-jawahar-blue.svg
        .. |Python-version-3| image:: https://img.shields.io/badge/Py-version-Python--3.5-green.svg
        .. |Build Status| image:: https://travis-ci.org/jawahar273/practNLPTools.svg?branch=master
           :target: https://travis-ci.org/jawahar273/practNLPTools
        .. |FOSSA Status| image:: https://app.fossa.io/api/projects/git%2Bhttps%3A%2F%2Fgithub.com%2Fjawahar273%2FpractNLPTools-lite.svg?type=small
           :target: https://app.fossa.io/projects/git%2Bhttps%3A%2F%2Fgithub.com%2Fjawahar273%2FpractNLPTools-lite?ref=badge_small
        
        
        .. Features
        .. --------
        
        .. * TODO
        
        Credits
        ---------
        
        This package was created with Cookiecutter_ and the `audreyr/cookiecutter-pypackage`_ project template.
        
        .. _Cookiecutter: https://github.com/audreyr/cookiecutter
        .. _`audreyr/cookiecutter-pypackage`: https://github.com/audreyr/cookiecutter-pypackage
        
        
        =======
        History
        =======
        
        0.2.0 pre-alpha
        ----------------
        * Marking standard tools for `pntl` 
        
        0.1.1 (2017-09-17)
        ------------------
        
        * Planing to release on PyPI.
        
Keywords: practNLPTools-lite senna python pntl pysenna
Platform: UNKNOWN
Classifier: Development Status :: 3 - Alpha
Classifier: Intended Audience :: Developers
Classifier: License :: OSI Approved :: MIT License
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 2
Classifier: Programming Language :: Python :: 2.6
Classifier: Programming Language :: Python :: 2.7
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3.3
Classifier: Programming Language :: Python :: 3.4
Classifier: Programming Language :: Python :: 3.5
Classifier: Topic :: Scientific/Engineering :: Information Analysis
