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Quiz Chapter 6 : Understanding Human Language

Total questions: 30

Worksheet time: 15mins

Name
Class
Date
1.

What is the main goal of Natural Language Processing (NLP)?

a)

To make computers communicate using programming languages

b)

To enable machines to understand and process human language

c)

To translate between computer codes

d)

To recognize only written language

2.

Which of the following is NOT a key NLP technique?

a)

Tokenization

b)

Stemming

c)

Lemmatization

d)

Compilation

3.

What does tokenization do?

a)

Removes stopwords

b)

Converts text into individual words or sentences

c)

Converts tokens into sound

d)

Combines multiple words into one

4.

In tokenization, which Python library is commonly used?

a)

nltk

b)

numpy

c)

matplotlib

d)

opencv

5.

What is the output of word_tokenize('AI is fun!')?

a)

['AI is fun']

b)

['AI', 'is', 'fun', '!']

c)

['AI', 'is', 'fun!']

d)

['AI_is_fun']

6.

Which type of tokenization divides text into sentences?

a)

word_tokenize

b)

sent_tokenize

c)

char_tokenize

d)

paragraph_tokenize

7.

Stemming reduces words to their:

a)

Base form

b)

Dictionary form

c)

Root form

d)

Original sentence

8.

The Porter Stemmer algorithm is used for:

a)

English language

b)

Bahasa Melayu

c)

Chinese

d)

French

9.

Which of the following may result from stemming?

a)

Only dictionary words

b)

Sometimes non-dictionary words

c)

Always verbs only

d)

Sentences

10.

Lemmatization differs from stemming because it:

a)

Is faster but less accurate

b)

Uses dictionary-based meaning for accurate base form

c)

Removes suffixes only

d)

Ignores word meaning

11.

Which component of NLP deals with the meaning of sentences?

a)

Syntactic analysis

b)

Semantic analysis

c)

Phonological analysis

d)

Morphological analysis

12.

What does syntactic analysis focus on?

a)

Grammar structure

b)

Word meaning

c)

Speaker intention

d)

Sentence context

13.

Pragmatic analysis helps understand:

a)

Grammar errors

b)

Intended meaning and context

c)

Word order

d)

Pronunciation

14.

Which is an example of ambiguity in NLP?

a)

Bank (finance or river?)

b)

AI stands for Artificial Intelligence

c)

I like pizza

d)

None

15.

The process of breaking text into words or sentences is called:

a)

Parsing

b)

Tokenization

c)

Lemmatization

d)

Encoding

16.

Which of the following is a challenge of NLP?

a)

Ambiguity

b)

Consistency

c)

Simplicity

d)

Automation

17.

Conversational agents include which of the following components?

a)

Speech recognition

b)

Dialogue processing

c)

Text-to-speech

d)

All of the above

18.

Why is NLP important in AI applications?

a)

It improves visual recognition

b)

It allows understanding of human language

c)

It replaces programming

d)

It stores data

19.

What happens when English stemmer is used on Bahasa Melayu words?

a)

Works perfectly

b)

Produces unchanged or incorrect results

c)

Translates to English

d)

Detects verbs only

20.

Which component focuses on sentence-to-sentence relationships in context?

a)

Phonological analysis

b)

Discourse analysis

c)

Semantic analysis

d)

Morphological analysis

21.

NLP enables machines to understand human language.

a)

True

b)

False

22.

Stemming always produces dictionary-valid words.

a)

True

b)

False

23.

Lemmatization is based on dictionary and context.

a)

True

b)

False

24.

Tokenization combines multiple words into one token.

a)

True

b)

False

25.

Ambiguity in NLP means one word or sentence may have multiple meanings.

a)

True

b)

False

26.

Phonological analysis deals with meaning of sentences.

a)

True

b)

False

27.

Syntactic analysis checks grammar structure.

a)

True

b)

False

28.

Pragmatic analysis focuses on literal word meanings only.

a)

True

b)

False

29.

NLP has no role in generative AI.

a)

True

b)

False

30.

Discourse analysis studies the relation between sentences.

a)

True

b)

False