NLTK :: Natural Language Toolkit
Aug 19, 2024 · NLTK is a leading platform for building Python programs to work with human language data. It provides easy-to-use interfaces to over 50 corpora and lexical resources such as WordNet, along with a suite of text processing libraries for classification, tokenization, stemming, tagging, parsing, and semantic reasoning, wrappers for industrial ...
NLTK :: Installing NLTK
NLTK requires Python versions 3.8, 3.9, 3.10, 3.11 or 3.12. For Windows users, it is strongly recommended that you go through this guide to install Python 3 successfully https://docs.python-guide.org/starting/install3/win/#install3-windows
1. Language Processing and Python - NLTK
1.1 Getting Started with Python One of the friendly things about Python is that it allows you to type directly into the interactive interpreter— the program that will be running your Python programs. You can access the Python interpreter using a simple graphical interface
NLTK Book
This version of the NLTK book is updated for Python 3 and NLTK 3. The first edition of the book, published by O'Reilly, is available at http://nltk.org/book_1ed/.
Example usage of NLTK modules
Sample usage for bleu Sample usage for bnc Sample usage for ccg Sample usage for ccg_semantics Sample usage for chat80 Sample usage for childes Sample usage for chunk ...
NLTK :: nltk package
StackDecoder Module contents nltk.tree package Submodules nltk.tree.immutable module ImmutableMultiParentedTree ImmutableParentedTree ImmutableProbabilisticTree ImmutableTree nltk.tree.parented module MultiParentedTree ParentedTree nltk.tree.parsing module bracket_parse() sinica_parse() nltk.tree.prettyprinter module TreePrettyPrinter nltk.tree ...
6. Learning to Classify Text - NLTK
... fori inrange(1, len(tokens)-1) iftokens[i] in'.?!' Using these featuresets, we can train and evaluate a punctuation classifier: >>> size = int(len(featuresets) * 0.1) >>> train_set, test_set = …
5. Categorizing and Tagging Words - NLTK
mentioned above for documentation. Initially we want to avoid the complications of these tagsets, so we use a built-in mapping to the "Universal Tagset": >>> …
7. Extracting Information from Text - NLTK
simply connects together NLTK's default sentence segmenter , word tokenizer , and part-of-speech tagger : >>> defie_preprocess(document): sentences = nltk.sent_tokenize(document) ... sentences = [nltk.word_tokenize(sent) forsent insentences] ... sentences = [nltk.pos_tag(sent) forsent insentences] Note Remember that our program samples assume you
Python Module Index - NLTK
Aug 19, 2024 · Python Module Indexa | b | c | d | f | g | h | i | j | l | m | n | p | s | t | u | w