PyNLPl, pronounced as 'pineapple', is a Python library for Natural Language Processing. It contains various modules useful for common, and less common, NLP tasks. PyNLPl can be used for example the computation of n-grams, frequency lists and distributions, language models. There are also more complex data types, such as Priority Queues, and search algorithms, such as Beam Search.
Project description
PyNLPl - Python Natural Language Processing Library
=====================================================
.. image:: https://travis-ci.org/proycon/pynlpl.svg?branch=master
:target: https://travis-ci.org/proycon/pynlpl
PyNLPl, pronounced as "pineapple", is a Python library for Natural Language
Processing. It is a collection of various independent or loosely interdependent
modules useful for common, and less common, NLP tasks. PyNLPl can be used for
example the computation of n-grams, frequency lists and distributions, language
models. There are also more complex data types, such as Priority Queues, and
search algorithms, such as Beam Search.
The library is a divided into several packages and modules. It works on Python
2.7, as well as Python 3.
The following modules are available:
- ``pynlpl.datatypes`` - Extra datatypes (priority queues, patterns, tries)
- ``pynlpl.evaluation`` - Evaluation & experiment classes (parameter search, wrapped
progressive sampling, class evaluation (precision/recall/f-score/auc), sampler, confusion matrix, multithreaded experiment pool)
- ``pynlpl.formats.cgn`` - Module for parsing CGN (Corpus Gesproken Nederlands) part-of-speech tags
- ``pynlpl.formats.folia`` - Extensive library for reading and manipulating the
documents in `FoLiA <http://proycon.github.io/folia>`_ format (Format for Linguistic Annotation).
- ``pynlpl.formats.fql`` - Extensive library for the FoLiA Query Language (FQL),
built on top of ``pynlpl.formats.folia``. FQL is currently documented `here
<https://github.com/proycon/foliadocserve>`_.
- ``pynlpl.formats.cql`` - Parser for the Corpus Query Language (CQL), as also used by
Corpus Workbench and Sketch Engine. Contains a convertor to FQL.
- ``pynlpl.formats.giza`` - Module for reading GIZA++ word alignment data
- ``pynlpl.formats.moses`` - Module for reading Moses phrase-translation tables.
- ``pynlpl.formats.sonar`` - Largely obsolete module for pre-releases of the
SoNaR corpus, use ``pynlpl.formats.folia`` instead.
- ``pynlpl.formats.timbl`` - Module for reading Timbl output (consider using
`python-timbl <https://github.com/proycon/python-timbl>`_ instead though)
- ``pynlpl.lm.lm`` - Module for simple language model and reader for ARPA
language model data as well (used by SRILM).
- ``pynlpl.search`` - Various search algorithms (Breadth-first, depth-first,
beam-search, hill climbing, A star, various variants of each)
- ``pynlpl.statistics`` - Frequency lists, Levenshtein, common statistics and
information theory functions
- ``pynlpl.textprocessors`` - Simple tokeniser, n-gram extraction
API Documentation can be found `here <http://pythonhosted.org/PyNLPl/>`_.
=====================================================
.. image:: https://travis-ci.org/proycon/pynlpl.svg?branch=master
:target: https://travis-ci.org/proycon/pynlpl
PyNLPl, pronounced as "pineapple", is a Python library for Natural Language
Processing. It is a collection of various independent or loosely interdependent
modules useful for common, and less common, NLP tasks. PyNLPl can be used for
example the computation of n-grams, frequency lists and distributions, language
models. There are also more complex data types, such as Priority Queues, and
search algorithms, such as Beam Search.
The library is a divided into several packages and modules. It works on Python
2.7, as well as Python 3.
The following modules are available:
- ``pynlpl.datatypes`` - Extra datatypes (priority queues, patterns, tries)
- ``pynlpl.evaluation`` - Evaluation & experiment classes (parameter search, wrapped
progressive sampling, class evaluation (precision/recall/f-score/auc), sampler, confusion matrix, multithreaded experiment pool)
- ``pynlpl.formats.cgn`` - Module for parsing CGN (Corpus Gesproken Nederlands) part-of-speech tags
- ``pynlpl.formats.folia`` - Extensive library for reading and manipulating the
documents in `FoLiA <http://proycon.github.io/folia>`_ format (Format for Linguistic Annotation).
- ``pynlpl.formats.fql`` - Extensive library for the FoLiA Query Language (FQL),
built on top of ``pynlpl.formats.folia``. FQL is currently documented `here
<https://github.com/proycon/foliadocserve>`_.
- ``pynlpl.formats.cql`` - Parser for the Corpus Query Language (CQL), as also used by
Corpus Workbench and Sketch Engine. Contains a convertor to FQL.
- ``pynlpl.formats.giza`` - Module for reading GIZA++ word alignment data
- ``pynlpl.formats.moses`` - Module for reading Moses phrase-translation tables.
- ``pynlpl.formats.sonar`` - Largely obsolete module for pre-releases of the
SoNaR corpus, use ``pynlpl.formats.folia`` instead.
- ``pynlpl.formats.timbl`` - Module for reading Timbl output (consider using
`python-timbl <https://github.com/proycon/python-timbl>`_ instead though)
- ``pynlpl.lm.lm`` - Module for simple language model and reader for ARPA
language model data as well (used by SRILM).
- ``pynlpl.search`` - Various search algorithms (Breadth-first, depth-first,
beam-search, hill climbing, A star, various variants of each)
- ``pynlpl.statistics`` - Frequency lists, Levenshtein, common statistics and
information theory functions
- ``pynlpl.textprocessors`` - Simple tokeniser, n-gram extraction
API Documentation can be found `here <http://pythonhosted.org/PyNLPl/>`_.
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.
Source Distribution
PyNLPl-0.7.3.2.tar.gz
(146.8 kB
view hashes)