{"id":130510,"date":"2022-12-13T14:21:52","date_gmt":"2022-12-13T14:21:52","guid":{"rendered":"https:\/\/blog.finxter.com\/?p=974815"},"modified":"2022-12-13T14:21:52","modified_gmt":"2022-12-13T14:21:52","slug":"python-split-text-into-sentences","status":"publish","type":"post","link":"https:\/\/sickgaming.net\/blog\/2022\/12\/13\/python-split-text-into-sentences\/","title":{"rendered":"Python | Split Text into Sentences"},"content":{"rendered":"\n
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\"\u2728\"Summary: <\/strong>There are four different ways to split a text into sentences:
\"\ud83d\ude80\" Using nltk<\/code> module
\"\ud83d\ude80\" Using re.split()
<\/code>\"\ud83d\ude80\" Using re.findall()<\/code>
\"\ud83d\ude80\" Using replace<\/code><\/p>\n

Minimal Example<\/strong><\/h3>\n
text = \"God is Great! I won a lottery.\" # Method 1\nfrom nltk.tokenize import sent_tokenize\nprint(sent_tokenize(text)) # Method 2\nimport re\nres = [x for x in re.split(\"[\/\/.|\/\/!|\/\/?]\", text) if x!=\"\"]\nprint(res) # Method 3\nres = re.findall(r\"[^.!?]+\", text)\nprint(res) # Method 4\ndef splitter(txt, delim): for i in txt: if i in delim: txt = txt.replace(i, ',') res = txt.split(',') res.pop() return res sep = ['.', '!']\nprint(splitter(text, sep)) # Output: ['God is Great', ' I won a lottery']<\/pre>\n
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Problem Formulation<\/h2>\n
Problem: <\/strong>Given a string\/text containing numerous sentences; How will you split the string into sentences?<\/p>\n
Example: <\/strong>Let\u2019s visualize the problem with the help of an example.<\/p>\n
# Input\ntext = \"This is sentence 1. This is sentence 2! This is sentence 3?\"\n# output\n['This is sentence 1', ' This is sentence 2', ' This is sentence 3']<\/pre>\n
Method 1: Using nltk.tokenize<\/a><\/strong><\/h2>\n
Natural Language Processing (NLP) has a process known as tokenization using which a large quantity of text can be divided into smaller parts called tokens. The Natural Language toolkit contains a very important module known as NLTK tokenize sentence<\/em><\/strong> which further comprises sub-modules. We can use this module and split a given text into sentences.<\/p>\n
Code:<\/strong><\/p>\n
from nltk.tokenize import sent_tokenize\ntext = \"This is sentence 1. This is sentence 2! This is sentence 3?\"\nprint(sent_tokenize(text)) # ['This is sentence 1.', ' This is sentence 2!', ' This is sentence 3?']<\/pre>\n
Explanation: <\/strong><\/p>\n