NLP_techniques.py

#Tokenisation, Lemmatising, Stemming, Corpus
import nltk
nltk.download()

#eg1
from nltk.tokenize import sent_tokenize, word_tokenize
sentence1 = "Ravi and Raj went for a walk"
print(word_tokenize(sentence1))

#eg2
print(sent_tokenize(sentence1))

#eg3
from nltk.corpus import stopwords
sentence2 = "Ravi and Raj went for a ride. Ravi and Raj went for a small ride"
stop = set(stopwords.words('english'))
Word = word_tokenize(sentence2)
Filtered_words = []
for i in Word:
    if i not in stop:
        Filtered_words.append(i)
print(Filtered_words)

#eg4
from nltk.stem import PorterStemmer
Words = ["cheer","cheering","cheerful"]
PS = PorterStemmer()
for word in Words:
    print(PS.stem(word))
    
#eg5
from nltk.stem import WordNetLemmatizer 
Lemmatise = WordNetLemmatizer() 
print("scare :", Lemmatise.lemmatize("scare")) 
print("hate :", Lemmatise.lemmatize("hate")) 
# a means adjective in pos.
print("worse :", lemmatise.lemmatize("worse", pos ="a"))

#eg6
import nltk.corpus
dir(nltk.corpus)
print(dir(nltk.corpus))