Natural Language Processing (NLP) MCQ (Quiz), W3Schools

1 .

What is Natural Language Processing (NLP)?

A)

An image editor

B)

A search engine

C)

A subfield of Computer science to understand and process natural language using AI

D)

None of the above

Correct Answer : A subfield of Computer science to understand and process natural language using AI

Explanation : A subfield of Computer science to understand and process natural language using AI

2 .

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

A)

To understand, interpret, and generate human language

B)

To generate random text

C)

To analyze only written text

D)

To automate data visualization

Correct Answer : To understand, interpret, and generate human language

3 .

What are the main challenge's of NLP?

A)

Handling POS-Tagging

B)

Handling Ambiguity of Sentences

C)

Handling Tokenization

D)

All of the above

Correct Answer : Handling Ambiguity of Sentences

Explanation : There are enormous ambiguity exists when processing natural language.

4 .

Which of the following includes major tasks of NLP?

A)

Automatic Summarization

B)

Machine Translation

C)

Discourse Analysis

D)

All of the above

Correct Answer : All of the above

5 .

What is Coreference Resolution?

A)

Anaphora Resolution

B)

Given a sentence or larger chunk of text, determine which words (�mentions�) refer to the same objects (�entities�)

C)

All of the mentioned

D)

None of the above

Correct Answer : Given a sentence or larger chunk of text, determine which words (�mentions�) refer to the same objects (�entities�)

Explanation : Anaphora resolution is a specific type of coreference resolution.

6 .

What is the purpose of tokenization in NLP?

A)

Removing stop words

B)

Analyzing sentiment

C)

Breaking text into words or phrases

D)

Identifying parts of speech

Correct Answer : Breaking text into words or phrases

7 .

Which library in Python is commonly used for NLP tasks?

A)

NLTK

B)

NumPy

C)

Matplotlib

D)

TensorFlow

Correct Answer : NLTK

8 .

What is stemming in NLP?

A)

Identifying named entities

B)

Analyzing grammatical structure

C)

Assigning sentiment scores to words

D)

Reducing words to their base or root form

Correct Answer : Reducing words to their base or root form

Explanation : Stemming is the process of reducing words to their base or root form.

9 .

Which algorithm is commonly used for text classification in NLP?

A)

Decision Trees

B)

Naive Bayes

C)

K-Means Clustering

D)

Support Vector Machines (SVM)

Correct Answer : Naive Bayes

Explanation : Naive Bayes is commonly used for text classification in NLP.

10 .

Which of the following is not a primary task of NLP?

A)

Image Recognition

B)

Text Classification

C)

Sentiment Analysis

D)

Named Entity Recognition

Correct Answer : Image Recognition

Explanation : Image recognition is not a primary task of NLP; it falls under computer vision.

11 .

What is TF-IDF in the context of NLP?

A)

A deep learning model

B)

A speech recognition method

C)

A feature extraction technique

D)

A sentiment analysis algorithm

Correct Answer : A feature extraction technique

Explanation : TF-IDF (Term Frequency-Inverse Document Frequency) is a feature extraction technique used in NLP.

12 .

Explain the concept of word embeddings in NLP.

A)

Categorizing words into classes

B)

Identifying named entities in a text

C)

Representing words as vectors in a continuous space

D)

Assigning numerical values to words based on their frequency

Correct Answer : Representing words as vectors in a continuous space

Explanation : Word embeddings involve representing words as vectors in a continuous space.

13 .

What is the Transformer architecture, and how does it contribute to NLP models?

A)

It is a feature extraction algorithm

B)

It is a rule-based system for semantic analysis

C)

It is a reinforcement learning model for text generation

D)

It is a neural network architecture that relies on attention mechanisms, improving the efficiency of NLP tasks

Correct Answer : It is a neural network architecture that relies on attention mechanisms, improving the efficiency of NLP tasks

Explanation : The Transformer architecture is a neural network architecture that relies on attention mechanisms, improving the efficiency of NLP tasks.

14 .

What is the purpose of named entity recognition (NER) in NLP?

A)

Tokenizing text

B)

Classifying text sentiment

C)

Identifying grammatical structure

D)

Recognizing entities such as names, locations, and organizations in text

Correct Answer : Recognizing entities such as names, locations, and organizations in text

Explanation : Named Entity Recognition (NER) is used to identify entities such as names, locations, and organizations in text.

15 .

Which metric is commonly used for evaluating the performance of classification models in NLP?

A)

F1 Score

B)

R-squared

C)

Mean Squared Error (MSE)

D)

Area Under the Curve (AUC)

Correct Answer : F1 Score

Explanation : The F1 Score is commonly used for evaluating the performance of classification models in NLP.

16 .

Which NLP task involves determining the grammatical structure of a sentence, including its parts of speech (e.g., noun, verb, adjective)?

A)

Sentiment Analysis

B)

Part-of-Speech Tagging

C)

Machine Translation

D)

Named Entity Recognition

Correct Answer : Part-of-Speech Tagging

17 .

In the context of NLP, what does the acronym 'POS' stand for?

A)

Part-of-Speech

B)

Positive Output

C)

Plain Old Search

D)

Preprocessed Object Store

Correct Answer : Part-of-Speech

18 .

What is Lexical Ambiguity in the context of NLP?

A)

Ambiguity of a sentence

B)

Ambiguity of phrase of a sentence

C)

Ambiguity of single word

D)

None of the above

Correct Answer : Ambiguity of single word

Explanation : Lexical Ambiguity refers to the ambiguity due to a single word. For example, a word Silver can be treated as a noun, adjective or as a verb.

19 .

What is Syntactic Ambiguity in the context of NLP?

A)

Ambiguity of single word

B)

Ambiguity of phrase of a sentence

C)

Both (A) and (B)

D)

Ambiguity of a sentence

Correct Answer : Ambiguity of a sentence

Explanation : When a sentence can be parsed in multiple ways, the ambiguity caused is termed as Syntactic Ambiguity. Consider the case in the following sentence, 'Man saw a boy with a magnifying glass'. Here the sentence is ambiguous as to whether the man saw a boy carrying a magnifying glass or man saw the boy with the help of a magnifying glass.

20 .

What is Anaphoric Ambiguity in the context of NLP?

A)

Ambiguity of a sentence

B)

Ambiguity of single word

C)

Ambiguity of phrase of a sentence

D)

None of the above

Correct Answer : None of the above

Explanation : Anaphoric ambiguity arises when anaphoric entities are used. Consider the following sentences. A goat rode up the hill. It was very steep. It reached quickly though. Here use of It causes anaphoric ambiguity.

21 .

What is Pragmatic Ambiguity in the context of NLP?

A)

Ambiguity of a sentence

B)

Ambiguity of single word

C)

Ambiguity of a context of phrase

D)

None of the above

Correct Answer : Ambiguity of a context of phrase

Explanation : Pragmatic ambiguity arises when the context of a sentence or phrase can be interpreted in many ways. Consider a case of 'I like you too' can be interpreted as 'I like you' as you like me or 'I like you' as anyone does.

22 .

Which of the following is true about Morphological Processing in the context of NLP?

A)

It is the first phase of NLP

B)

It breaks the chunks of language into tokens

C)

Both (A) and (B)

D)

None of the above

Correct Answer : Both (A) and (B)

Explanation : Morphological Processing is the first phase of NLP. Main purpose of Morphological processing is to break the chunks of the language to tokens corresponding to words, sentences or paragraphs. For example, 'uneasy' can be divided into a subword token as 'un-easy'.

23 .

Which of the following correctly defines right-most derivation?

A)

Sentential form of an input is scanned and replaced from left to right

B)

Sentential form of an input is scanned and replaced from right to the left

C)

Both (A) and (B)

D)

None of the above

Correct Answer : Sentential form of an input is scanned and replaced from right to the left

Explanation : Sentential form or more specifically right sentential form of an input is scanned and replaced from right to the left in right-most derivation.

24 .

Which NLP technique involves converting words into their base or dictionary form, reducing them to their root form?

A)

Lemmatization

B)

Sentiment Analysis

C)

Part-of-Speech Tagging

D)

Named Entity Recognition

Correct Answer : Lemmatization

25 .

What is the primary goal of Sentiment Analysis in NLP?

A)

To perform tokenization

B)

To identify the sentiment of a text

C)

To perform machine translation

D)

To recognize and classify named entities (e.g., names, locations)

Correct Answer : To identify the sentiment of a text

26 .

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)

Sentiment Analysis

C)

Part-of-Speech Tagging

D)

Named Entity Recognition

Correct Answer : Stemming

27 .

What is the primary goal of Machine Translation in NLP?

A)

To perform tokenization

B)

To identify the sentiment of a text

C)

To recognize and classify named entities (e.g., names, locations)

D)

To translate text from one language to another

Correct Answer : To translate text from one language to another

28 .

Which of the following correctly defines left-most derivation?

A)

Sentential form of an input is scanned and replaced from left to right

B)

Sentential form of an input is scanned and replaced from right to the left

C)

Both (A) and (B)

D)

None of the above

Correct Answer : Sentential form of an input is scanned and replaced from left to right

Explanation : Sentential form or more specifically left sentential form of an input is scanned and replaced from left to the right in left-most derivation

29 .

Which of the following correctly defines Top-Down parser?

A)

Top-Down Parser starts parsing the tree from the start symbol, constructing the tree up to the input symbol

B)

Top-Down Parser starts parsing from the input symbol and constructs the tree up to the start symbol

C)

Both (A) and (B)

D)

None of the above

Correct Answer : Top-Down Parser starts parsing the tree from the start symbol, constructing the tree up to the input symbol

Explanation : Top-Down Parser starts parsing the tree from the start symbol, constructing the tree up to the input symbol. Top-Down parser uses a recursive procedure to process the inputs.

30 .

Which of the following correctly defines Bottom-Up parser?

A)

Bottom-Down Parser starts parsing the tree from the start symbol, constructing the tree up to the input symbol

B)

Bottom-Down Parser starts parsing from the input symbol and constructs the tree up to the start symbol

C)

Both (A) and (B)

D)

None of the above

Correct Answer : Bottom-Down Parser starts parsing from the input symbol and constructs the tree up to the start symbol

Explanation : Bottom-Down Parser starts parsing the input symbol and constructs the tree up to the start symbol.

31 .

Which of the following correctly defines the role of a parser?

A)

A Parser reports any syntax error

B)

A Parser creates a parse tree

C)

A Parser recovers from a common error to continue processing of the rest of the program

D)

All of the above

Correct Answer : All of the above

Explanation : A Parser is a software component which takes text as input and gives structural representation of input after checking it against the grammar of the language. Main roles of a parser are following:

* To report any syntax error.
* To recover from commonly occurring errors to continue parsing of the rest of the program.
* To create a parse tree
* To create a symbol tree
* To produce intermediate representations.

32 .

Which NLP task involves converting text from one language to another while preserving its meaning and context?

A)

Sentiment Analysis

B)

Part-of-Speech Tagging

C)

Machine Translation

D)

Named Entity Recognition

Correct Answer : Machine Translation

33 .

What is the primary use of a 'corpus' in Natural Language Processing (NLP)?

A)

To generate random text

B)

To store and analyze a collection of texts

C)

To perform machine translation

D)

To identify the sentiment of a text

Correct Answer : To store and analyze a collection of texts

34 .

In NLP, what does 'TF-IDF' stand for?

A)

Term Frequency-Inverse Document Frequency

B)

Token Frequency-Inverted Data Field

C)

Term Frequency-Information Document Format

D)

Text Feature Indexing-Inverted Dictionary Format

Correct Answer : Term Frequency-Inverse Document Frequency

35 .

Which NLP task involves determining the structure of a document, such as extracting headings, paragraphs, and sections?

A)

Machine Translation

B)

Part-of-Speech Tagging

C)

Named Entity Recognition

D)

Document Summarization

Correct Answer : Document Summarization

36 .

What is the primary goal of Document Summarization in NLP?

A)

To identify the sentiment of a text

B)

To perform tokenization

C)

To generate a concise and coherent summary of a document

D)

To recognize and classify named entities (e.g., names, locations)

Correct Answer : To generate a concise and coherent summary of a document

37 .

In NLP, what is the purpose of 'stopwords'?

A)

To improve text readability

B)

To group words into topics

C)

To perform machine translation

D)

To identify the sentiment of a text

Correct Answer : To improve text readability

38 .

What is the primary goal of Text Mining in NLP?

A)

To improve text readability

B)

To perform tokenization

C)

D)

To analyze and extract structured information from unstructured text

Correct Answer : To analyze and extract structured information from unstructured text

Explanation : To identify the sentiment of a text

39 .

In NLP, what is the purpose of a 'stemmer'?

A)

To recognize named entities

B)

To reduce words to their root form

C)

To group words into topics

D)

To split text into individual words or tokens

Correct Answer : To reduce words to their root form

40 .

In NLP, what is the purpose of 'syntax parsing'?

A)

To improve text readability

B)

To perform tokenization

C)

To generate random text

D)

To analyze the grammatical structure of a sentence

Correct Answer : To analyze the grammatical structure of a sentence

41 .

Which NLP technique involves transforming words into numerical vectors, capturing semantic relationships between words?

A)

Semantic Analysis

B)

Sentiment Analysis

C)

Word Embeddings

D)

Named Entity Recognition

Correct Answer : Word Embeddings

42 .

What is the primary use of 'word embeddings' in NLP?

A)

To improve text readability

B)

To generate random words

C)

To represent words as numerical vectors

D)

To perform tokenization

Correct Answer : To represent words as numerical vectors

43 .

Which NLP task involves generating human-like text or speech in response to a given input, often used in chatbots and virtual assistants?

A)

Text Generation

B)

Sentiment Analysis

C)

Dependency Parsing

D)

Named Entity Recognition

Correct Answer : Text Generation

44 .

Which of the following is a Syntactic TreeBank Corpus?

A)

Sinina

B)

Penn Arabic TreeBank

C)

Columbia Arabic TreeBank

D)

All of the above

Correct Answer : All of the above

Explanation : Penn Arabic Treebank, Columbia Arabic Treebank are syntactic Treebanks in Arabia language. Sininca is a syntactic Treebank in Chinese language. Lucy, Susane and BLLIP WSJ syntactic treebank corpus in English language.

45 .

Which of the following is a Semantic TreeBank Corpus?

A)

Groningen Meaning Bank

B)

Geoquery

C)

Robot Commands TreeBanks

D)

All of the above

Correct Answer : Groningen Meaning Bank

Explanation : Robot Commands Treebank, Geoquery, Groningen Meaning Bank, RoboCup Corpus are popular Semantic Treebanks.

46 .

Which of the following are valid types of TreeBank Corpus?

A)

Semantic TreeBanks

B)

Syntactic TreeBanks

C)

Both (A) and (B)

D)

None of the above

Correct Answer : Both (A) and (B)

Explanation : Semantic TreeBanks and Syntactic TreeBanks are the most common types of TreeBanks.Semantic TreeBank uses formal representation of semantic structure of sentences. Syntactic TreeBank uses expressions of formal language retrieved from parsed treebank data.

47 .

Which of the following is an element of Corpus Design?

A)

Sampling

B)

Corpus Size

C)

Corpus Balance

D)

All of the above

Correct Answer : All of the above

Explanation : Corpus Balance, Sampling and Corpus Size all are integral parts of a Corpus Design. Corpus balance refers to the wide range of the text categories as representatives of the language. Sampling is used to get a subset of data which can be used to represent the large set of information and Corpus Size represents the size of the Corpus.

48 .

In NLP, what does the acronym 'NLG' stand for?

A)

Named Language Grammar

B)

Natural Language Generator

C)

Natural Language Guidelines

D)

Named Language Generation

Correct Answer : Natural Language Generator

49 .

Which NLP technique involves analyzing and extracting structured information from documents and web pages?

A)

Information Extraction

B)

Named Entity Recognition

C)

Text Classification

D)

Dependency Parsing

Correct Answer : Information Extraction

50 .

What is the primary use of a 'syntax tree' in NLP?

A)

To perform tokenization

B)

To represent the hierarchical structure of a document

C)

To identify the sentiment of a text

D)

To recognize and classify named entities (e.g., names, locations)

Correct Answer : To represent the hierarchical structure of a document

51 .

In NLP, what does the term 'bag of words' (BoW) refer to?

A)

A collection of dictionaries

B)

A method for detecting named entities

C)

A syntax tree representation of a document

D)

A representation of a text as a set of unique words

Correct Answer : A representation of a text as a set of unique words

52 .

Which NLP task involves determining the structure and relationships between words in a sentence, typically used in question-answering systems?

A)

Sentiment Analysis

B)

Text Classification

C)

Dependency Parsing

D)

Named Entity Recognition

Correct Answer : Dependency Parsing

53 .

What is the primary goal of 'question-answering systems' in NLP?

A)

To improve text readability

B)

To perform tokenization

C)

To understand and answer questions based on text

D)

To generate random questions

Correct Answer : To understand and answer questions based on text

54 .

Which NLP task involves determining the language in which a text document is written?

A)

Language Identification

B)

Sentiment Analysis

C)

Named Entity Recognition

D)

Document Summarization

Correct Answer : Language Identification

55 .

What is the primary goal of 'Topic Modeling' in NLP?

A)

To generate random text

B)

To perform tokenization

C)

To improve text readability

D)

To extract underlying themes or topics

Correct Answer : To extract underlying themes or topics

Natural Language Processing (NLP) - MCQ(Quiz)