================== practNLPTools-lite

This project is a fork of biplab-iitb_

.. _biplab-iitb: https://github.com/biplab-iitb/practNLPTools

.. warning::

CLI is only for example purpose don't use for long running jobs.

Get the very old code in devbranch_ or prior stable version oldVersion_.

|Author| |python_version| |HitCount|

|Build Status| - this built might take you to practNLPTools_ which is testing ground for this repository so don’t worry.

Practical Natural Language Processing Tools for Humans. practNLPTools is a pythonic library over SENNA_ and Stanford Dependency Extractor.

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• Documentation docs1_ and docs2_

.. _docs1: https://pntl.readthedocs.io .. _docs2: https://htmlpreview.github.io/?https://raw.githubusercontent.com/jawahar273/practNLPTools-lite/master/docs/index.html

.. note:: After version 0.3.0+ pntl should able to store the result into database for later usage if needed by installing below dependency.

pip install git+https://github.com/jawahar273/snowbase.git

QuickStart

Downlarding Stanford Parser JAR

To downlard the stanford-parser from github automatically and placing them inside the install direction.

.. code:: bash

pntl -I true

downlards required file from github.

Running Predefine Examples Sentences

To run predefine example in batch mode(which has more than one list of examples).

.. code:: bash

pntl -SE home/user/senna -B true

Example

Batch mode means listed sentences.

..code::

# Example structure for predefine
# Sentences in the code.

sentences = [
    "This is line 1",
    "This is line 2",

]

To run predefine example in non batch mode.

.. code:: bash

pntl -SE home/user/senna

Running user given sentence

To run user given example using -S is

.. code:: bash

pntl -SE home/user/senna -S 'I am gonna make him an offer he can not refuse.'

Functionality

• Semantic Role Labeling.
• Syntactic Parsing.
• Part of Speech Tagging (POS Tagging).
• Named Entity Recognisation (NER).
• Dependency Parsing.
• Shallow Chunking.
• Skip-gram(in-case).
• find the senna path if is install in the system.
• stanford parser and depPaser file into installed direction.

Future work

• tag2file(new)
• 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 #. Automatic finds stanford parsing jar if it is present in install path[pntl].

.. 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.

**Linux:**

run:

::

    sudo python setup.py install 

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 | +-----------------+-----------------+-----------------+

.. note::

This benchmark may diffrent from system to sytem. The result produced here is from ububtu 4Gb RAM and i3 process.

.. _practNLPTools: https://github.com/jawahar273/practNLPTools-lite .. _SENNA: http://ronan.collobert.com/senna/ .. _oldVersion: https://github.com/jawahar273/practNLPTools-lite/tree/pyup-update-pytest-3.2.2-to-3.2.3 .. _devbranch: https://github.com/jawahar273/practNLPTools-lite/tree/dev

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.. 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