NLP Natural Language Processing MCQ's




Question 1 :
Number,person,gender and case agreements are examples of which types of constraints on reference resolution?

  1. semantic
  2. lexical
  3. discourse
  4. syntactic
  

Question 2 :
In the sentence, 'They bought a blue house ', the underlined part is an example of _____.

  1. Noun phrase
  2. Verb phrase
  3. Prepositional phrase
  4. Adverbial phrase
  

Question 3 :
Many words have more than one meaning; selecting the sensible meaning in context is done with

  1. Randomization
  2. Shallow semantic analysis
  3. Word Sense Disambiguation
  4. POS tagging
  

Question 4 :
_____________ is the process of understanding if a given text is talking positively or negatively about a given subject (e.g. for brand monitoring purposes).

  1. Syntactical analysis
  2. Hybrid analysis
  3. Sentiment Analysis
  4. Lexical analysis
  

Question 5 :
Which of the follwing is an appication of NLP?

  1. Summarizing a text or article
  2. Designing mobile computing
  3. front page designing
  4. Database designing
  

Question 6 :
I Saw The Boy With A Pony Tail , What Type Of Ambiguity Does Sentence Have

  1. Semantic Ambiguity
  2. Pragmetic Ambiguity
  3. Structured Ambiguity
  4. Simplex
  

Question 7 :
1.The Tank Was Full Of Water.. I Saw The Military Tank.Here Tank Is Used In Different Context, Which Type Of Ambiguity Is This?

  1. Semantic Ambiguity
  2. Syntactic Ambiguity
  3. Anaphoric Ambiguity
  4. Syntactical Ambiguity
  

Question 8 :
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 9 :
How to compute probability of a sentence or sequence of sentence in N-gram model?

  1. P(W) = P(W1,W2, W3,…, Wn)
  2. P(W) = P(Wn+1|Wn-1)
  3. P(W) = P(Wn-1| Wn+1)
  4. P(W) = P(Wn+1 | Wn)
  

Question 10 :
___________ can also specify the results of processes described by utterances in a discourse.

  1. Pronouns
  2. demonstratives
  3. generics
  4. inferrables
  

Question 11 :
Ir System : Subset Of Documents : : ? : Subset Of Information Within Document

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

Question 12 :
What is the single morpheme of word Boxes?

  1. Box
  2. Boxes
  3. Boxses
  4. Boxing
  

Question 13 :
Which of the following is efficient representation of text data?

  1. Bag of Word
  2. TF-IDF
  3. Word Vector
  4. BERT
  

Question 14 :
Lexical semantics deals with_________

  1. Meaning of word
  2. internal structure of words
  3. relationship between the words
  4. All a,b,c
  

Question 15 :
Pronouns usually refer to entities that were introduced no further than one or two sentences back in the ongoing discourse, whereas ________________ can often refer further back.

  1. demonstratives
  2. indefinite noun phrase
  3. one anaphora
  4. definite noun phrases
  

Question 16 :
The Cat flys after applying which ngram gives the output as The Cat,Cat flys

  1. Unigram
  2. Bigram
  3. Trigram
  4. Quadrigrams
  

Question 17 :
Techniques not used in phrases extraction

  1. Part of speech tagging
  2. Statistical phrase extraction
  3. Hybrid
  4. Decompounding
  

Question 18 :
How many different lexemes are there in the following list?man, men, girls, girl, mouse

  1. 1
  2. 2
  3. 3
  4. 4
  

Question 19 :
I Bought A Printer Today. The Printer Didn'T Work Properly. What Type Of Reference In The Discourse Context Is Done In This Statement?

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

Question 20 :
Distance measure used to calculate semantic similarity between words is ____

  1. Cosine Similarity
  2. Manhattan Distance
  3. Euclidean Distance
  4. Levenshtein Distance
  

Question 21 :
To identify the category of each word in a sentence

  1. Parsing
  2. POS
  3. Semantic Analysis
  4. Pragmatics
  

Question 22 :
This type of automata maps between two sets of symbols.

  1. DFA
  2. Turing Machine
  3. FST
  4. NFA
  

Question 23 :
Morphological Segmentation _______________

  1. Does Discourse Analysis
  2. Separate words into individual morphemes and identify the class of the morphemes
  3. Is an extension of propositional logic
  4. Is an extension of propositional limit
  

Question 24 :
Discourse Analysis Involves The Study Of Relationship Between?

  1. Programming Language And Contextual Foreground
  2. Language And Dictionary Background
  3. Dictionary And Knowledge
  4. Language And Contextual Background
  

Question 25 :
To find relevance of word in a document technique used

  1. TF-IDF
  2. Lemma
  3. Tokenizer
  4. Pos tagging
  

Question 26 :
Which sentence describes inflectional morphology?

  1. Adding a morpheme to produce a new word but the same lexeme.
  2. Adding a morpheme to produce a new word and different lexeme.
  3. Adding a morpheme to produce the same word but different lexeme.
  4. Adding a morpheme to produce the same sentence but different lexeme.
  

Question 27 :
In which class, new words are added all the time

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

Question 28 :
What is output of Morhological analysis for the input word 'mice'?

  1. mice N SG
  2. mouse N SG
  3. mouse N PL
  4. mice N PL
  

Question 29 :
Which of the following is a kind of text summarization?

  1. Topic-based summarization
  2. Extraction-based summarization
  3. History-based summarization
  4. Summarizing a text or article
  

Question 30 :
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
  
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