Natural Language Processing MCQ

home MCQ Questions & Answer


Question 351 : Which one of the following models can not perform text classification

  1. Naive Bayes
  2. SVM
  3. K-means
  4. OLAP
  

Question 352 : CFG captures -----------------------------.

  1. Constituency and ordering
  2. word meaning
  3. relation between words
  4. sentence meaning
  

Question 353 : Number of states require to accept string ends with 10.

  1. 3
  2. 2
  3. 1
  4. can’t be represented.
  

Question 354 : Is Inflectional morphology performed in google translation?

  1. Performed
  2. Not performed
  3. Partly performed
  4. Depends on situation
  

Question 355 : _____________________ is a group of words that may behave as a single unit or phrase.

  1. Constituency
  2. Grammatical Relation
  3. Sub-categorization
  4. Dependancies
  

Question 356 : Summarization which creates new phrases paraphrasing the original source.

  1. Extraction-based
  2. Abstraction-based
  3. Auto-correct
  4. None
  

Question 357 : ______has the same spelling and sound, but do not have related meanings

  1. Homophones
  2. Polysemy
  3. Homonymy
  4. Synonymy
  

Question 358 : Which of the following belongs to the open class group?

  1. Verb
  2. Prepositions
  3. Determinents
  4. Conjunctions
  

Question 359 : An anaphoric reference...

  1. Helps the text make sense
  2. Links forward to another part of the text
  3. Refers back to another part of the text
  4. Give us information about time and place
  

Question 360 : Polysemy is defined as the coexistence of multiple meanings for a word or phrase in a text object. Which of the following models is likely the best choice to correct this problem?

  1. Random Forest Classifier
  2. Convolutional Neural Networks
  3. Gradient Boosting
  4. Keyword Hashing
  

Question 361 : In syntax analysis the input is provded from

  1. Morphology Analysis
  2. Phonology Analysis
  3. Semantics Analysis
  4. Pragmatic Analyis
  

Question 362 : Which Is The Type Of Morphology That Changes The Word Category And Affects The Meaning

  1. Inflectional
  2. Derivational
  3. Cliticization
  4. Rational
  

Question 363 : The area of AI that investigates methods of facilitating communication between people and computers is:

  1. natural language processing
  2. symbolic processing
  3. decision support
  4. robotics
  

Question 364 : instead of thinking of words as containers of meaning, we look at the "roles" they fulfill within the situation described by a sentence

  1. semantic roles (thematic roles)
  2. semantic features
  3. Semantic roles
  4. semantically; syntactically
  

Question 365 : Stochastic tagger also known as….........

  1. HM tagger
  2. RMM tagger
  3. HMM tagger
  4. Super tagger
  

Question 366 : Morphotactics is a model of

  1. Spelling modifications that may occur during affixation
  2. All affixes in the English language
  3. How and which morphemes can be affixed to a stem
  4. Ngrams of affixes and stems
  

Question 367 : Which of the following is a single valued attribute

  1. Register_number
  2. Address
  3. SUBJECT_TAKEN
  4. Reference
  

Question 368 : Which class words are limited in number

  1. Open class
  2. Closed class
  3. Tree bank
  4. Dictionary
  

Question 369 : Which best describes the English language?

  1. English has complex morphology and less rigid syntax.
  2. English has less complex morphology but more rigid syntax.
  3. English has complex morphology and rigid syntax.
  4. English has complex morphology
  

Question 370 : Suppose a language model assigns the following conditional n-gram probabilities to a 3-word test set: 1/4, 1/2, 1/4. Then P(test-set) = 1/4 * 1/2 * 1/4 = 0.03125. What is the perplexity?

  1. 0.25
  2. 0.03125
  3. 32
  4. 3.175
  

Question 371 : Named Entity Recognition means:

  1. Finding spans of text that constitute proper names and then classifying the type of the entity.
  2. Mapping between name and entity.
  3. Classification of text into subject and predicates.
  4. Searching text for proper nouns.
  

Question 372 : In An Hmm, Observation Likelihoods Measure

  1. The Likelihood Of A Pos Tag Given A Word
  2. The Likelihood Of A Pos Tag Given The Preceding Tag
  3. The Likelihood Of A Word Given A Pos Tag
  4. The Likelihood Of A Pos Tag Given Two Preceding Tags
  

Question 373 : Conjunctions are used to ______ two phrases, clauses, or sentences

  1. Separate
  2. Identify
  3. Distinguish
  4. Join
  

Question 374 : "I want an early upgrade" What is the type of word class for word "want" ?

  1. Verb
  2. Determinant
  3. Personal Pronoun
  4. Adjective
  

Question 375 : The basic operation of a web browser is to pass a request to the web server. This request is an address for a web page and is known as the:

  1. UAL: Universal Address Locator
  2. HTML: Hypertext Markup Language
  3. URL: Universal Resource Locator
  4. HTTP: Hypertext transfer protocol
  

Question 376 : FST cannot work as _____________

  1. recognizer
  2. generator
  3. translator
  4. lexicon
  

Question 377 : Choose from the following where NLP is not being useful.

  1. Automatic Text Summarization
  2. Automatic Question-Answering Systems
  3. Partially Observable systems
  4. Information Retrieval
  

Question 378 : Which One Of The Following Is Not A Pre-Processing Technique In Nlp

  1. Converting To Lowercase
  2. Removing Punctuations
  3. Removal Of Stop Words
  4. Sentiment Analysis
  

Question 379 : N-Gram language models cannot be used for -------.

  1. Spelling Correction
  2. Predicting the completion of a sentence
  3. Removing semantic ambiguity
  4. Speech Recognition
  

Question 380 : e.g. 'walk', 'talk', 'print' are examples of which type of verb

  1. Regular verb
  2. Irregular verb
  3. Complex verb
  4. Normal verb
  

Question 381 : In POS, using discriminative approach, direction of flow is from class to words

  1. Yes
  2. No
  3. Depends on sentence
  4. Randomly
  

Question 382 : One of the main challenges of NLP Is _____________.

  1. Handling Ambiguity of Sentences
  2. Handling Tokenization
  3. Handling POS-Tagging
  4. All of the mentioned
  

Question 383 : Word-Right , Word-Write are

  1. Homophones
  2. Homograph
  3. Synonyms
  4. Antonyms
  

Question 384 : Given A Sentence S="W1 W2 W3 … Wn", To Compute The Likelihood Of S Using A Bigram Model. How Would You Compute The Likelihood Of S?

  1. Calculate The Conditional Probability Of Each Word In The Sentence Given The Preceding Word And Add The Resulting Numbers
  2. Calculate The Conditional Probability Of Each Word In The Sentence Given The Preceding Word And Multiply The Resulting Numbers
  3. Calculate The Conditional Probability Of Each Word Given All Preceding Words In A Sentence And Add The Resulting Numbers
  4. Calculate The Conditional Probability Of Each Word Given All Preceding Words In A Sentence And Multiply The Resulting Numbers
  

Question 385 : Where does the Hidden Markov Model is used?

  1. Speech recognition
  2. Understanding of real world
  3. Both Speech recognition & Understanding of real world
  4. Understanding of real world images
  

Question 386 : “I went to the school, and they told me come on next day”. What type of ambiguity present in the given sentence?

  1. Syntactic ambiguity
  2. Anaphoric ambiguity
  3. Semantic ambiguity
  4. Lexical ambiguity
  

Question 387 : Which Application Of Nlp Allows Querying A Structured Database Using Natural Language Sentences?

  1. Speech Recognition
  2. Natural Language Interfaces To Db
  3. Information Extraction
  4. Information Retrieval
  

Question 388 : In the English language derivational morphemes can be...

  1. Prefixes ,Suffixes,Infixes
  2. Prefixes ,Suffixes
  3. Infixes only
  4. Suffixes only
  

Question 389 : Which of the following pair represents Antonomy lexical relation?

  1. (fat, thin)
  2. (crow,bird)
  3. (window, door)
  4. (head,nose)
  

Question 390 : Which of the following NLP tasks use sequential labeling technique?

  1. POS tagging
  2. Named entity recognition
  3. Speech recognition
  4. POS tagging & Named Entity Recognition & Speech recognition
  

Question 391 : How many types of Deixis eixsts?

  1. 3
  2. 5
  3. 4
  4. 2
  

Question 392 : Which of the following computer language is used for artificial intelligence?

  1. FORTRAN
  2. PROLOG
  3. C
  4. COBOL
  

Question 393 : What is Machine Translation?

  1. Converts one human language to another
  2. Converts human language to machine language
  3. Converts any human language to English
  4. Converts Machine language to human language
  

Question 394 : Which is the true in NLP study?

  1. Machine learning is a subdivision of deep learning.
  2. Shallow learning is the simplest form of deep learning.
  3. Deep learning is a subdivision of machine learning.
  4. NLP is the acronym for Neural Language Processing.
  

Question 395 : How many lexemes are there in following list.man,men,girls,girl,mouse

  1. 4
  2. 5
  3. 3
  4. 2
  

Question 396 : Given A Sequence Of Observations And A Hmm Model, Which Of The Following Fundamental Problems Of Hmm Finds The Most Likely Sequence Of States That Produced The Observations In An Efficient Way?

  1. Evaluation Problem
  2. Likelihood Estimation Problem
  3. Decoding Problem
  4. Learning Problem
  

Question 397 : Which is not the main challenges in machine translation?

  1. Word Translation
  2. Phrase Translation
  3. Syntactic Translation
  4. Special Characters Translation
  

Question 398 : Solve the equation according to the sentence “I am planning to visit New Delhi to attend Analytics Vidhya Delhi Hackathon”. A = (# of words with Noun as the part of speech tag) B = (# of words with Verb as the part of speech tag) C = (# of words with frequency count greater than one) What are the correct values of A, B, and C?

  1. 5,5,2
  2. 5,5,0
  3. 7,5,1
  4. 7,4,2
  

Question 399 : Which of the following will be POS Tagger output when the input sentence is "And now for something completely different"?

  1. [('And', 'CC'), ('now', 'RB'), ('for', 'IN'), ('something', 'RB'), ('completely', 'RB'), ('different', 'JJ')]
  2. [('And', 'CC'), ('now', 'RB'), ('for', 'IN'), ('something', 'NN'), ('completely', 'JJ'), ('different', 'RB')]
  3. [('And', 'CC'), ('now', 'RB'), ('for', 'IN'), ('something', 'NN'), ('completely', 'RB'), ('different', 'JJ')]
  4. "[('And', 'CC'), ('now', 'RB'), ('for', 'CC'), ('something', 'NN'), ('completely', 'RB'), ('different', 'JJ')]"
  

Question 400 : "Make Computers As They Can Solve Problems Like Humans And Think Like Humans " Is

  1. Challege Of Nlp
  2. Disadvantage Of Nlp
  3. Stage Of Nlp
  4. Knowledge Of Nlp