[Python NLTK] Tutorial: Get started easily and have fun with natural language processing

1. Introduction to NLTK

NLTK is a Natural Language ProcessingTools package for the pythonprogramming language, created in 2001 by Steven Bird and Edward Loper . NLTK provides a wide range of text processing tools, including text preprocessing, word segmentation, part-of-speech tagging, syntactic analysis, semantic analysis, etc., which can help developers easily process natural language data.

NLTK can be installed with the following command:

from nltk.tokenize import Word_tokenize

text = "Hello, world! This is a sample text."
tokens = word_tokenize(text)

print(tokens)

Output:

from nltk.tokenize import sent_tokenize

text = "Hello, world! This is a sample text. This is another sentence."
sentences = sent_tokenize(text)

print(sentences)

Output:

from nltk.tag import pos_tag

text = "The cat sat on the mat."
tagged_text = pos_tag(text)

print(tagged_text)

Output:

from nltk.parse import CoreNLPParser

parser = CoreNLPParser()

text = "The cat sat on the mat."
tree = parser.parse(text)

print(tree)

Output:

from nltk.corpus import wordnet

text = "The cat sat on the mat."

# 查找"cat"的同义词
synsets = wordnet.synsets("cat")
for synset in synsets:
print(synset)

# 查找"sat"的反义词
antonyms = wordnet.antonyms("sat")
for antonym in antonyms:
print(antonym)

Output:

Synset("cat.n.01")
Synset("big_cat.n.01")
Synset("domestic_cat.n.01")
...
Antonym("sit.v.01")

Python NLTK is a powerful, easy-to-use natural language processing toolkit that can help you easily analyze and process natural language data. This article introduces the basic usage of NLTK and lets you quickly master natural language processing skills through demonstration code. If you are interested in natural language processing, you might as well try NLTK. I believe you will find its powerful capabilities.

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