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 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.
• 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 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.