NLP Natural Language Processing MCQ's




Question 241 :
Which is correct option

  1. Pragmatics is one of the approach of discourse analysis
  2. Discourse Analysis is Study of utterance meaning
  3. A and B Both
  4. None of them
  

Question 242 :
Where did the first recognisable NLP application developed ?

  1. At Birkbeck College, London
  2. At IBM Research.
  3. At Thomas College , Newyork
  4. At the University of America
  

Question 243 :
Knowledge of the relationship of meaning to the goals and intentions of the speaker is

  1. Morphology
  2. Semantics
  3. Pragmatics
  4. Discourse
  

Question 244 :
What are the possible input of an NLP system?

  1. Speech and noise
  2. Speech ,scan document and Written Text
  3. Noise and Written Text
  4. Noise and value
  

Question 245 :
I Bought A Printer Today. I Had Bought One Earlier In004. This One Cost Me Rs. 6000 Whereas That One Cost Me Rs.2000. In This Statement, This And That Are Known As Which Type Of Reference In The Discourse Context?

  1. Definite Refernce
  2. Indefinite Reference
  3. Pronominal Refenece
  4. Demonstrative Reference
  

Question 246 :
Conceal - cover is a example of ________

  1. Antonym
  2. Synonym
  3. Polysemy
  4. Homonym
  

Question 247 :
Clock = digital - analog - alarm

  1. Polysemy
  2. Meronymy
  3. Hyponymy
  4. Cline
  

Question 248 :
For HMM Model, with N hidden states, V observable states, what is the dimension of State Transition Probability Matrix

  1. N×V
  2. N×1
  3. N×N
  4. 1For HMM Model, with N hidden states, V observable states, what is the dimension of Emission Probability ×N
  

Question 249 :
Which Of The Following Technique Is Not A Part Of Flexible Text Matching?

  1. Soundex
  2. Metaphone
  3. Edit Distance
  4. Keyword Hashing
  

Question 250 :
Identify the POS tag for the word nice in following sentence It was indeed a nice night?

  1. JJ
  2. JJR
  3. JJS
  4. RB
  

Question 251 :
Natural language understanding is used in:

  1. natural language interfaces
  2. natural language front ends
  3. text understanding systems
  4. All of the mentioned
  

Question 252 :
TF-IDF helps in …....

  1. Finding the most frequently occurring word in the document
  2. Spelling Corrections
  3. Stemming and Lemmatization
  4. Removing stop words in the document
  

Question 253 :
Famous PYTHON NLP Toolkit is

  1. NLTK
  2. Panda
  3. Stanford Core NLP
  4. spacy
  

Question 254 :
Which derivational prefixes does not change the category of word to which they are attached?

  1. Re- - -Un
  2. -er
  3. -ize
  4. -ing
  

Question 255 :
What is transformation based learning?

  1. A machine learning technique,in which rules are automatically induced from the data.
  2. A machine learning technique,in which rules are manually induced from the data.
  3. A machine learning technique,in which rules are transformed into another data.
  4. A machine learning technique,in which rules are not used.
  

Question 256 :
__ involves resolving words to their dictionary form

  1. Overstemming
  2. Understemming
  3. Lemmatization
  4. NER
  

Question 257 :
How many trigrams phrases can be generated from the following sentence, after performing following text cleaning steps: Stopword Removal, Replacing punctuations by a single space? '#Coursera is a great platform to learn @Machine Learning.'?

  1. 3
  2. 4
  3. 5
  4. 6
  

Question 258 :
_____ is a process of assigning corresponding part of speech like noun, verb, adverb, adjective, verb to each word in a sentence.

  1. Part of speech tagging
  2. Name entity tagging
  3. Parsing
  4. Disambiguation
  

Question 259 :
What is irony

  1. Using language to signal attitude other than what has been literally said.
  2. Using words that are context bound
  3. A mixture of vague language and humour
  4. The process of deriving implied meanings.
  

Question 260 :
Which one of the following is TRUE about CRF (Conditional Random Field) and HMM (Hidden Markov Model)?

  1. CRF is generative model and HMM is discriminative model
  2. Both CRF and HMM are generative model
  3. CRF is discriminative model and HMM is generative model
  4. Both CRF and HMM are discriminative model
  

Question 261 :
Typically the first or preliminary model of something, especially from which other forms are developed; helps explain the meaning of certain words e.g. (furniture__>desk, table) is called as_________

  1. Prototype
  2. Metonymy
  3. Hyponym
  4. Homonyms
  

Question 262 :
A web link within a web page that references another part of the same page is called a:

  1. Out link
  2. Vector
  3. In link
  4. Tendril
  

Question 263 :
One way we organize our knowledge of words is on the basis of ___ (words that frequently occur together).We commonly associate certain words with other words. (Family Feud-esque, but with ONE word)

  1. collocation
  2. homophones
  3. location
  4. denotation
  

Question 264 :
The list of web pages that a web crawler has queued up to index is called the:

  1. Web Page Queue
  2. Seed set
  3. URL Filter
  4. URL Frontier
  

Question 265 :
Assume That There Are0000 Documents In A Collection. Out Of These, 50 Documents Contain The Terms 'Difficult Task'. If 'Difficult Task' Appears Times In A Particular Document, What Is The Tfidf Value Of The Terms For That Document?

  1. 8.11
  2. 15.87
  3. Zero
  4. 81.1
  

Question 266 :
Consider the following given sentences. Match the lexical relations between the first word (w​1​) to the second word (w​2​) i.e. w​1​ is a of w​2. * Invention of the wheel​ is one of the landmarks in the history of mankind. * Companies are trying to make driverless car. * Golden daffodils​ are fluttering and dancing in the breeze. * Mumbai has unique flower ​park. 1. Holonym __> i.wheel-car 2. Hyponym __> ii. car-wheel 3. Meryonym __> iii. daffodils-flower 4. Hypernym __> iv. flower- daffodils

  1. 1-iii, 2-ii, 3-iv, 4-i
  2. 1-ii, 2-iii, 3-i, 4-iv
  3. 1-ii, 2-iii, 3-iv, 4-i
  4. 1-i, 2-ii, 3-iii, 4-iv
  

Question 267 :
______ System consists of collection of grammar rules, dictionary, and software programs to process the rules.

  1. Direct translation
  2. Knowledge based Machine Translation
  3. Rule based translation
  4. Example Based translation
  

Question 268 :
The words bank/data bank/blood bank is an example of ________

  1. Homophony
  2. Synonymy
  3. Polysemy
  4. Hyponymy
  

Question 269 :
In Probability Ranking Principal, Ranking documents in order of ____________ probability of relevance is optimal.

  1. Increasing
  2. Decreasing
  3. Anyway
  4. Steady
  

Question 270 :
An optimizer Compiler

  1. Is optimized to occupy less space
  2. Both of the mentioned
  3. Optimize the code
  4. None of the mentioned
  
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