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.
1 maintainer
Metadata
1 maintainer
Release files for PyNLPl 0.7.3.5
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
|---|---|---|---|
| PyNLPl-0.7.3.5.tar.gz | 147.4 kB | Details |
Release files / PyNLPl-0.7.3.5.tar.gz
| Download URL | PyNLPl-0.7.3.5.tar.gz |
|---|---|
| Size | 147.4 kB |
| Tags | Source |
|
SHA-256 checksum How to use checksums |
460a101895ae73044babf56ef86b09d77c332fdb7f84ff1fcc1cff6c361cad8f
|
|
BLAKE2b-256 checksum How to use checksums |
b5751bfd6635ed6d6f76e09fbc4966c2465c71f55a8a66ee8372c6f885bb1590
|
| Upload date | |
|
Uploaded using Trusted Publishing? What is trusted publishing? |
No |
