Stemming (Porter, Snowball) in NLP - Interactive Code Practice

Practice - 5 Tasks

1fill in blank

easy

Complete the code to create a Porter stemmer object.

NLP

from nltk.stem import [1]
porter = [1]()

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APorterStemmer

BSnowballStemmer

CWordNetLemmatizer

DLancasterStemmer

Attempts:

3 left

💡 Hint

Common Mistakes

Using SnowballStemmer instead of PorterStemmer

Trying to import WordNetLemmatizer which is for lemmatization, not stemming

The PorterStemmer class from nltk.stem is used to create a Porter stemmer object.

2fill in blank

medium

Complete the code to stem the word 'running' using the Porter stemmer.

NLP

word = 'running'
stemmed_word = porter.[1](word)
print(stemmed_word)

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Atokenize

Bstem

Clemmatize

Dparse

Attempts:

3 left

💡 Hint

Common Mistakes

Using lemmatize() method which is not available in PorterStemmer

Using tokenize() or parse() which are unrelated to stemming

The stem() method is used to get the stem of a word using the Porter stemmer.

3fill in blank

hard

Fix the error in the code to create a Snowball stemmer for English.

NLP

from nltk.stem import SnowballStemmer
stemmer = SnowballStemmer('[1]')

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Agerman

Bspanish

Cfrench

Denglish

Attempts:

3 left

💡 Hint

Common Mistakes

Using capitalized language names like 'English'

Using a language different from the intended one

The SnowballStemmer requires the language name as a lowercase string. For English, use 'english'.

4fill in blank

hard

Fill both blanks to stem the word 'happiness' using SnowballStemmer for English.

NLP

from nltk.stem import [1]
stemmer = [1]('[2]')
print(stemmer.stem('happiness'))

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ASnowballStemmer

BPorterStemmer

Cenglish

Dspanish

Attempts:

3 left

💡 Hint

Common Mistakes

Using PorterStemmer with a language argument (it does not take one)

Using 'spanish' instead of 'english' for the language

Use SnowballStemmer and specify the language as 'english' to stem English words.

5fill in blank

hard

Fill all three blanks to create a dictionary of stemmed words from a list using PorterStemmer.

NLP

from nltk.stem import [1]
porter = [1]()
words = ['running', 'jumps', 'easily']
stemmed = {word: porter.[2](word) for word in [3]
print(stemmed)

Drag options to blanks, or click blank then click option'

APorterStemmer

Bstem

Cwords

DSnowballStemmer

Attempts:

3 left

💡 Hint

Common Mistakes

Using SnowballStemmer instead of PorterStemmer

Using lemmatize() instead of stem()

Using a variable name other than words in the loop

Import and create a PorterStemmer object, then use its stem() method to stem each word in the list words.