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NLP-WEEK2-B1

Total questions: 10

Worksheet time: 5mins

Name
Class
Date
1.

What is stemming in NLP?

a)
  • Assigning sentiment scores to words

b)
  • Analyzing grammatical structure

c)
  • Reducing words to their base or root form

d)
  • Identifying named entities

2.

In Python's NLTK library, what function is used for stop word removal?

a)
  • remove_stopwords()

b)
  • stopwords.remove()

c)
  • nltk.corpus.stopwords.words()

d)
  • nltk.remove_stopwords()

3.

which NLP technique involves reducing words to their root form by removing suffixes and prefixes,even if the result is not a valid word

a)

stemming

b)

pats-of-speech

c)

sentiment analysis

d)

NER

4.

In NLP what is the purpose of "stopwords"

a)

To improve the text readability

b)

To identify the sentiment of a text

c)

To group words into topics

d)

To perform machine translation

5.

What is the primary goal of Information Retrieval in NLP

a)

To recognise and classify named entities

b)

To identify the sentiment of a text

c)

To retrieve relevant documents based on user queries

d)

To perform Tokenization

6.

The root form of a word in Wordnet dictionary is called

a)

stem

b)

sense

c)

gloss

d)

lemma

7.

In NLP, The process of removing words like “and”, “is”, “a”, “an”, “the” from a sentence is called as

a)

stemming

b)

lemmatization

c)

stopwords

d)

all of the above

8.

In which step of the Porter Stemmer Algorithm are suffixes like "ATIONAL" transformed into "ATE"?

a)

step 2

b)

step 3

c)

it is removed

d)

none of the above

9.

Identify odd one out

a)

scikit learn

b)

spacy

c)

bert

d)

nltk

10.

Which one of the following is keyword Normalization techniques in NLP

a)

Stemming

b)

Lemmatization

c)

parts of speech

d)

Named entity recognition