28th
May
NLP MCQ

NLP MCQ

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  • 28th May, 2021
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NLP MCQ Quiz

Following are mostly asked Nlp MCQ test that are designed for professionals like you to crack you interviews. You can take this Nlp online test before appearing to you real interview. This Nlp quiz there are around 30+ multiple choice questions on Nlp with four options.

1) What is full form of NLP?

  • A. Nature Language Processing
  • B. Natural Language Process
  • C. Natural Language pages
  • D. Natural Language Processing

2) How many Components of NLP are there?

  • A. 3
  • B. 4
  • C. 5
  • D. 2

3) What is full form of NLG?

  • A. Natural Language Genes
  • B. Natural Language Growth
  • C. Natural Language Generator
  • D. Natural Language Generation

4) Which of the following includes major tasks of NLP?

  • A. Machine Translation
  • B. Automatic Summarization
  • C. Discourse Analysis
  • D. All of the above

5) Which of the following is used to mapping sentence plan into sentence structure?

  • A. Text planning
  • B. Sentence planning
  • C. None of the Above
  • D. Text Realization
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6) How many steps of NLP is there?

  • A. 4
  • B. 3
  • C. 6
  • D. 5

7) In linguistic morphology _____________ is the process for reducing inflected words to their root form

  • A. Rooting
  • B. Text-Proofing
  • C. Both Rooting & Stemming
  • D. Stemming

8) Which of the following is demerits of Top-Down Parser?

  • A. inefficient
  • B. It is hard to implement
  • C. none of the Above
  • D. Slow speed

9) He lifted the beetle with red cap. contain which type of ambiguity ?

  • A. Lexical ambiguity
  • B. Referential ambiguity
  • C. None of the Above
  • D. Syntax Level ambiguity

10) Given a sound clip of a person or people speaking, determine the textual representation of the speech

  • A. Text-to-speech
  • B. Both A and B
  • C. None of the Above
  • D. Speech-to-text

11) What is Machine Translation?

  • A. Converts human language to machine language
  • B. Converts any human language to English
  • C. Converts Machine language to human language
  • D. Converts one human language to another

12) I am tired. Contain which type of ambiguity ?

  • A. Sementic ambiguity
  • B. Syntax Level ambiguity
  • C. Lexical ambiguity
  • D. None of the Above

13) Which of the following is merits of Context-Free Grammar?

  • A. They are highly precise
  • B. High speed
  • C. All of the above
  • D. simplest style of grammar

14) Many words have more than one meaning; we have to select the meaning which makes the most sense in context. This can be resolved by ____________

  • A. Fuzzy Logic
  • B. Shallow Semantic Analysis
  • C. All of the above
  • D. Word Sense Disambiguation

15) Parts-of-Speech tagging determines ___________

  • A. part-of-speech for each word dynamically as per meaning of the sentence
  • B. part-of-speech for each word dynamically as per sentence structure
  • C. all part-of-speech for a specific word given as input
  • D. All of the above

16) Which of the following is used study of construction of words from primitive meaningful units?

  • A. Phonology
  • B. Shonology
  • C. Morpheme
  • D. Morphology

17) What is Morphological Segmentation?

  • A. None of the Above
  • B. is an extension of propositional logic
  • C. Does Discourse Analysis
  • D. Separate words into individual morphemes and identify the class of the morphemes

18) What is the main challenges of NLP?

  • A. Handling Tokenization
  • B. Handling POS-Tagging
  • C. All of the above
  • D. Handling Ambiguity of Sentences

19) What is full form of NLU?

  • A. Nature Language Understanding
  • B. Natural Long Understanding
  • C. None of the Above
  • D. Natural Language Understanding

20) What are the input and output of an NLP system?

  • A. Speech and noise
  • B. Noise and Written Text
  • C. Noise and value
  • D. Speech and Written Text

21) What will be the perplexity value if you calculate the perplexity of an unsmoothed language model on a test corpus with unseen words?

  • A. 0
  • B. any non-zero value
  • C. None of the above
  • D. Infinity

22) Which of the following NLP tasks use sequential labeling technique?

  • A. Speech recognition
  • B. Named Entity Recognition
  • C. POS tagging
  • D. All of the above

23) In NLP, The algorithm decreases the weight for commonly used words and increases the weight for words that are not used very much in a collection of documents

  • A. Term Frequency (TF)
  • B. Word2Vec
  • C. Latent Dirichlet Allocation (LDA)
  • D. Inverse Document Frequency (IDF)

24) Which of the below are NLP use cases?

  • A. Speech Biometric
  • B. Facial Recognition
  • C. Detecting objects from an image
  • D. Text Summarization

25) Which one of the following are keyword Normalization techniques in NLP

  • A. Part of Speech
  • B. Named entity recognition
  • C. Lemmatization
  • D. Stemming

26) Dissimilarity between words expressed using cosine similarity will have values significantly higher than 0.5

  • A. FALSE
  • B. TRUE

27) Which of the text parsing techniques can be used for noun phrase detection, verb phrase detection, subject detection, and object detection in NLP.

  • A. Continuous Bag of Words
  • B. Skip Gram and N-Gram extraction
  • C. Part of speech tagging
  • D. Dependency Parsing and Constituency Parsing

28) What are the possible features of a text corpus in NLP?

  • A. Basic Dependency Grammar
  • B. Part of Speech Tag
  • C. Vector notation of the word
  • D. All of the above

29) Which of the following techniques can be used to compute the distance between two word vectors in NLP?

  • A. Lemmatization
  • B. Cosine Similarity
  • C. N-grams
  • D. Euclidean distance

30) Which of the following techniques can be used for keyword normalization in NLP, the process of converting a keyword into its base form?

  • A. Soundex
  • B. Cosine Similarity
  • C. N-grams
  • D. Lemmatization

31) which of the following options show where nlp is useful?

  • A. Information Retrieval
  • B. Automatic Text Summarization
  • C. Automatic Question-Answering Systems
  • D. All of the above

Nlp Online Test Questions (Nlp FAQs)

1) What is NLP?

NLP stands for Natural Language Processing. NLP is a subpart of Artificial intelligence that helps machines by processing and understanding the human language to perform repetitive tasks automatically.

2) List major components of NLP?

Major components of NLP are:

  • Morphological and Lexical Analysis.
  • Syntactic Analysis.
  • Semantic Analysis.
  • Discourse Integration.
  • Pragmatic Analysis.

3) What is tokenization in NLP?

Tokenization is the process of dividing or splitting phrases, sentences, paragraphs, or entire text document into smaller units such that each token will hold an individual division.

4) What is Numpy Slicing?

Numpy Slicing is a method used for accessing the specific parts of a string, list, or tuple. It can be performed like this: element[start:end: step], where the element can be string, list, or tuple.

5) What is Lemmatization?

Lemmatization in Natural Language Processing is a text pre-processing technique used for grouping different words together to their base root with the use of vocabulary and morphological analysis.

6) What is NLTK?

NLTK stands for Natural Language Toolkit. NLTK is basically a platform that helps in building a python program for working with High-Level Language data. It helps the computer in understanding, analyzing, and processing the written text.

7) What is pragmatic analysis in NLP?

The pragmatic analysis is the process of extracting information from text with the help of a set of linguistic and logical tools to figure out the real meaning of the text.

8) What is perplexity?

Perplexity is a method of analyzing and evaluating language models in NLP i.e. it evaluates the probability distribution over a sentence or whole text.

9) What is POS tagging?

POS (Part of Speech) tagging is used to categorize each word in a sentence according to its appropriate part of speech and other grammatical categories.

10) What is Wordnet?

WordNet is the lexical database or dictionary in Natural Language Tool Kit (NLTK) that is specifically designed to get information about the words and phrases.

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