Import libraries.

  Tokenize the sentence in the sample text.

  Tokenize the words in every sentences.

  Remove the stopwords.

  Do speech tagging for words.

  Print the results.

import nltk
from nltk.corpus import stopwords
from nltk.tokenize import word_tokenize, sent_tokenize
stop_words = set(stopwords.words(‘english’))

#sample text
text = “Python is a scripting interpreted and object oriented language”
print(“Original text”)
print(text)

def speech_tagging(text):

tokenized = sent_tokenize(text)
for i in tokenized:

#Word tokenizers
wordsList = nltk.word_tokenize(i)

#removing stop words from wordList
wordsList = [w for w in wordsList if not w in stop_words]

# Using a Tagger. Which is part-of-speech
tagged = nltk.pos_tag(wordsList)

print(“\n”)
print(“After speech tagging”)
print(tagged)
speech_tagging(text)