Pattern has tools for natural language processing like part-of-speech taggers, n-gram search, sentiment analysis, WordNet.It supports machine learning vector space model, clustering, SVM.

Website:

https://github.com/clips/pattern

TextBlob is a Python library for processing textual data. It provides a simple API for diving into common natural language processing tasks such as part-of-speech tagging, noun phrase extraction, sentiment analysis, classification, translation, and more.

Gensim is a Python library for topic modelling, document indexing and similarity retrieval with large corpora. It can process input larger than RAM. According to the author it is "the most robust, efficient and hassle-free piece of software to realize unsupervised semantic modelling from plain text

Python Natural Language Processing Library(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

Installation:

#Linux

sudo apt-get install pymol

# Fedora

yum install pymol

It’s commercial open source software. Industrial strength NLP with Python and Cython. Its a pipeline for fast, state-of-the-art natural language processing.

Website:

https://spacy.io

Polyglot is a natural language pipeline that supports massive multilingual applications. It supports tokenization for 165 languages, Language detection for 196 languages, Named Entity Recognition for 40 languages, Part of Speech Tagging for 16 languages, Sentiment Analysis for 136 languages, Word Embeddings for 137 languages, Morphological analysis for 135 languages, Transliteration for 69 languages

Website:

https://pypi.python.org/pypi/polyglot 

MontyLingua is a free, commonsense-enriched, end-to-end natural language understander for English. Feed raw English text into MontyLingua, and the output will be a semantic interpretation of that text. Perfect for information retrieval and extraction, request processing, and question answering. From English sentences, it extracts subject/verb/object tuples, extracts adjectives, noun phrases and verb phrases, and extracts people's names, places, events, dates and times, and other semantic information

Website:

http://web.media.mit.edu/~hugo/montylingua/

Website