- nltk.book
- nltk.cfg: Basic data classes for representing context free grammars.
- nltk.chat: A class for simple chatbots.
- nltk.chunk: Classes and interfaces for identifying non-overlapping linguistic
groups (such as base noun phrases) in unrestricted text.
- nltk.classify: Classes and interfaces for labeling tokens with category labels (or
class
labels).
- nltk.cluster: This module contains a number of basic clustering algorithms.
- nltk.compat: Backwards compatibility with previous versions of Python.
- nltk.containers
- nltk.corpus: NLTK corpus readers.
- nltk.data: Functions to find and load NLTK resource
files, such as corpora, grammars, and saved processing objects.
- nltk.decorators: Decorator module by Michele Simionato <michelesimionato@libero.it>
Copyright Michele Simionato, distributed under the terms of the BSD License (see below).
- nltk.detect: Functions for detecting a token's features.
- nltk.draw: Tools for graphically displaying and interacting with the objects
and processing classes defined by the Toolkit.
- nltk.etree
- nltk.evaluate: Utility functions for evaluating processing modules.
- nltk.featstruct: Basic data classes for representing feature structures, and for
performing basic operations on those feature structures.
- nltk.inference: Classes and interfaces for theorem proving and model building.
- nltk.internals
- nltk.misc
- nltk.model
- nltk.olac
- nltk.parse: Classes and interfaces for producing tree structures that represent
the internal organization of a text.
- nltk.probability
- nltk.sem: This package contains classes for representing semantic structure
in formulas of first-order logic and for evaluating such formulas
in set-theoretic models.
- nltk.sem.drt
- nltk.sem.drt_resolve_anaphora: This module performs the anaphora resolution functionality for
DRT.py.
- nltk.sem.evaluate: This module provides data structures for representing first-order
models.
- nltk.sem.logic: A version of first order predicate logic, built on top of the
untyped lambda calculus.
- nltk.sem.relextract: Code for extracting relational triples from the ieer and conll2002
corpora.
- nltk.sem.util: Utility functions for batch-processing sentences: parsing and
extraction of the semantic representation of the root node of the
the syntax tree, followed by evaluation of the semantic
representation in a first-order model.
- nltk.stem: Interfaces used to remove morphological affixes from words, leaving
only the word stem.
- nltk.tag: Classes and interfaces for tagging each token of a sentence with
supplementary information, such as its part of speech.
- nltk.tag.api: Interface for tagging each token in a sentence with supplementary
information, such as its part of speech.
- nltk.tag.brill: Brill's transformational rule-based tagger.
- nltk.tag.crf: An interface to Mallet's Linear Chain Conditional Random Field
(LC-CRF) implementation.
- nltk.tag.hmm: Hidden Markov Models (HMMs) largely used to assign the correct
label sequence to sequential data or assess the probability of a
given label and data sequence.
- nltk.tag.sequential: Classes for tagging sentences sequentially, left to right.
- nltk.tag.simplify
- nltk.tag.util
- nltk.test: Unit tests for the NLTK modules.
- nltk.text
- nltk.tokenize: Functions for tokenizing, i.e., dividing text strings into
substrings.
- nltk.tree: Class for representing hierarchical language structures, such as
syntax trees and morphological trees.
- nltk.treetransforms: A collection of methods for tree (grammar) transformations used in
parsing natural language.
- nltk.util
- nltk.wordnet: Wordnet interface, based on Oliver Steele's Pywordnet, together
with an implementation of Ted Pedersen's Wordnet::Similarity
package.
- nltk.yamltags
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