What is Lemmatization?

B) Mapping words to their dictionary base form

Which technique helps machines disambiguate words with multiple meanings based on context?

● B) Word Sense Disambiguation

Which of the following is an example of Tokenization?

B) Splitting a sentence into words

What is a “corpus” in NLP?

C) Cutting words down to their root form

What does “speech-to-text” involve in NLP?

C) Converting spoken language in

Which of the following best describes stemming?

C) Cutting words down to their root form

What is the main goal of Natural Language Processing?

● C) Enable machines to understand and process human language

Which of these is an example of Machine Translation?

B) Translating a sentence from English to French

What is Named Entity Recognition (NER)?

B) Identifying proper nouns and categorizing them (like names, places)

What is the purpose of semantic analysis in NLP?

B) Interpret the meaning of words and sentences

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NLP QUIZ CYBERSECURITY

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Questions 20

Answers

1
What is Lemmatization?
D) Counting how many times a word appears
B) Mapping words to their dictionary base form
A) Removing punctuation
C) Removing irrelevant sentences
2
Which of the following tasks is best solved using NLP?
A) Finding the shortest path in a graph
B) Summarizing a long article
C) Predicting stock market trends
D) Rendering 3D graphics
3
Which technique helps machines disambiguate words with multiple meanings based on context?
● B) Word Sense Disambiguation
C) Lemmatization
A) Tokenization
D) OCR
4
Which of the following is an example of Tokenization?
C) Removing stop words
A) Converting text to lowercase
D) Counting characters
B) Splitting a sentence into words
5
In which NLP step are common words like “the,” “is,” and “and” often removed?
C) Stop Word Removal
D) Stemming
B) Named Entity Recognition
A) Parsing
6
Which technique is commonly used to detect the emotion behind a text?
C) Tokenization
A) Parsing
B) Sentiment Analysis
D) Lemmatization
7
What is a “corpus” in NLP?
C) Cutting words down to their root form
B) Removing special characters
A) Grouping sentences
● D) Reordering paragraphs
8
What does “speech-to-text” involve in NLP?
D) Translating code between languages
A) Reading QR codes
B) Converting written words into audio
C) Converting spoken language in
9
What does POS tagging stand for?
B) Parts of Syntax
C) Part-of-Speech tagging
A) Positioning of Speech
● D) Parsing of Semantics
10
Which language model was among the first to show the power of Transformers in NLP?
B) CNN
A) GPT ✅
C) Naive Bayes
D) ResNet
11
Which of the following best describes stemming?
D) Reordering paragraphs
A) Grouping sentences
B) Removing special characters
C) Cutting words down to their root form
12
Which of the following is an application of NLP?
A) Image segmentation
C) Hardware debugging
B) Sentiment analysis
D) Pathfinding algori
13
What is the main goal of Natural Language Processing?
● B) Analyze financial data
● C) Enable machines to understand and process human language
A) Convert images into text
Build new programming languages
14
Which of these is an example of Machine Translation?
D) Converting text to speech
C) Recognizing handwriting
A) Siri answering a question
B) Translating a sentence from English to French
15
What is Named Entity Recognition (NER)?
C) Detecting the language of the text
A) Finding grammatical errors
B) Identifying proper nouns and categorizing them (like names, places)
D) Summarizing long paragraphs
16
What does NLP stand for?
Natural Language Processing
Natural Linguistic Parising
Neural Learning Program
Networked Language Protocol
17
Which model architecture is widely used in recent NLP advancements?
D) K-Means Clustering
● C) Transformer
B) Convolutional Neural Network
A) Decision Tree
18
What is the purpose of semantic analysis in NLP?
C) Convert text into binary
A) Identify sentence boundaries
B) Interpret the meaning of words and sentences
D) Sort documents alphabetically
19
In which real-world scenario is NLP NOT typically used?
D) Voice assistants
B) Autocorrect
A) Chatbots
● C) Weather forecasting
20
Which one is NOT a typical stage in an NLP pipeline?
A) Tokenization
B) POS tagging
C) Compilation
D) Parsing

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