Natural Language Processing MCQ

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Question 251 : The linker

  1. Is similar to interpreter
  2. Uses source code as its input
  3. I s required to create a load module
  4. None of the mentioned
  

Question 252 : Which Of The Following Architecture Can Be Trained Faster And Needs Less Amount Of Training Data

  1. Lstm Based Language Modelling
  2. Transformer Architecture
  3. Word Sense Disambiguation
  4. N-Grams
  

Question 253 : _______ Is used to decode the optimal tag sequence

  1. Early algorithm
  2. Viterbi algorithm
  3. Lexk algorithm
  4. A centering algorithm
  

Question 254 : Solve the equation according to the sentence “I am planning to visit New York to attend International Film Fare Festival”. 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, 2002
  2. 5, 5, 2002
  3. 7, 5, 2001
  4. 7, 4, 2001
  

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 : Select the correct statements related to "Grammatical polarity"

  1. The grammatical category associated with affirmative and negative is called polarity
  2. The process of converting affirmative to negative is called negation
  3. All of the mentioned
  4. None of the mentioned
  

Question 257 : What Is The Name For Information Sent From Robot Sensors To Robot Controllers?

  1. Temperature
  2. Pressure
  3. Feedback
  4. Signal
  

Question 258 : It is not example of text summaries

  1. Headlines
  2. Outlines
  3. Digest
  4. Corpus
  

Question 259 : It is not step of text summarization.

  1. Convert the paragraph into sentences
  2. Text processing
  3. Evaluate the weighted occurrence frequency of the words
  4. Categorization
  

Question 260 : What Is Full Form Of Nlg?

  1. Natural Language Generation
  2. Natural Language Genes
  3. Natural Language Growth
  4. Natural Language Generator
  

Question 261 : Which of the text parsing techniques can be used for noun phrase detection, verb phrase detection, subject detection, and object detection in NLP.

  1. Part of speech tagging
  2. Skip Gram and N-Gram extraction
  3. Continuous Bag of Words
  4. Dependency Parsing and Constituency Parsing
  

Question 262 : The statement “Which team won the match?” can be represented as

  1. N->Wh-NP VP
  2. S->Wh-NP VP
  3. VP->Wh-NP VP
  4. S->Wh-NP NP
  

Question 263 : Characterizing the meaning of words in terms of its relationship to other words such as synonymy, antonymy, and hyponymy is called ________________.

  1. Lexical relationship
  2. Semantic analysis
  3. Collocation
  4. Gradable antonyms
  

Question 264 : Which is not the Classification levels in Sentiment Analysis

  1. Document-level
  2. Character-level
  3. Aspect-level
  4. Sentence-level
  

Question 265 : 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 266 : "Sunder Pichal is the CEO of Google having headquarter in California" , How many named entities exist in above sentence

  1. 4
  2. 2
  3. 3
  4. 1
  

Question 267 : Selecting the appropriate speech act strategies and the linguistic forms for realizing it depends on

  1. the social status and the culture of the interlocutors
  2. their age
  3. their social distance
  4. All of these
  

Question 268 : In this sentence: “...no benefits justify the risk of nuclear weapons...I will explain why nuclear technology has a future on our planet despite its dangers.” Which type of lexical cohesion can you find?

  1. Hyponymy
  2. Synonymy
  3. Antonymy
  4. Hyponymy
  

Question 269 : The study of which words occur together, and their frequency of co-occurrence is called as _______.

  1. Connotation
  2. Collocation
  3. Implication
  4. Location
  

Question 270 : In CFG,terminals mainly correspond to ...............while pre-terminals mainly correspond to ........

  1. Characters in the langauge, POS tags
  2. Words in the language, POS categories
  3. Words in the language,word relations
  4. Lexemes, POS Tags
  

Question 271 : Which is example of homophony?

  1. be-bee
  2. be-bo
  3. be-by
  4. be-bio
  

Question 272 : What Is The Major Difference Between Crf (Conditional Random Field) And Hmm (Hidden Markov Model)?

  1. Crf Is Generative Whereas Hmm Is Discriminative Model
  2. Crf Is Discriminative Whereas Hmm Is Generative Model
  3. Crf And Hmm Are Generative Model
  4. Crf And Hmm Are Discriminative Model
  

Question 273 : The metric to measure “the intensity of emotion provoked by the stimulus” in emotion modeling is:

  1. Severity
  2. Valence
  3. Arousal
  4. Dominance
  

Question 274 : A verb phrase cannot have a

  1. a verb followed by an NP {VP → Verb NP}
  2. a verb followed by a PP {VP → Verb PP}
  3. a verb followed by two NPs {VP → Verb NP NP}
  4. a verb followed by two APs {VP → Verb AP AP}
  

Question 275 : The words Blood bank, Sperm bank and Egg bank are the example of,

  1. Polysemy
  2. Hypernym
  3. Antonym
  4. Metonymy
  

Question 276 : "I Saw Two Laser Printers In A Shop. They Were The Fastest Printers Available". In This Statement, "They" Is Known As Which Type Of Reference In The Discourse Context?

  1. Generic Refernce
  2. Indefinite Reference
  3. Quantifier/Ordinal Refenece
  4. Demonstrative Reference
  

Question 277 : Given A Sound Clip Of A Person Or People Speaking, Determine The Textual Representation Of The Speech.

  1. Text-To-Speech
  2. Speech-To-Text
  3. Text
  4. Speech
  

Question 278 : Which Approach Does Direct Translation Use?

  1. No Approach
  2. Word By Word Translation
  3. Sentential Translation
  4. Paragraph By Paragraph Translation
  

Question 279 : Which algorithm is used for solving temporal probabilistic reasoning?

  1. Hill-climbing search
  2. Hidden markov model
  3. Depth-first search
  4. Breadth-first search
  

Question 280 : The performance of an utterance and its meaning

  1. positive face
  2. perlocutionary act
  3. locutionary act
  4. illocutionary act
  

Question 281 : In text summarisation an ___________ uses different words to describe the contents of the document.

  1. Abstract
  2. Extract
  3. Information
  4. Prose
  

Question 282 : "I Met This Girl Earlier In A Conference." In This Statement, "This" Is Known As Which Type Of Reference In The Discourse Context?

  1. Definite Refernce
  2. Indefinite / Non-Anaphoric Reference
  3. Pronominal Refenece
  4. Demonstrative Reference
  

Question 283 : "John and Mary love their Acuras. They drive them all the time". It is example of _______

  1. Indefinte noun pharse
  2. Definte noun pharse
  3. Demostrative
  4. Discontinuous sets
  

Question 284 : In linguistic morphology, _____________ is the process for reducing inflected words to their root form.

  1. Rooting
  2. Stemming
  3. Text-Proofing
  4. Proofing
  

Question 285 : Which one of the following statement is false?

  1. The CFG can be converted to Chomsky normal form
  2. The CFG can be converted to Greibach normal form
  3. CFG is accepted by pushdown automata
  4. CFG is accepted by Chomsky normal form
  

Question 286 : In information retrieval, extremely common words which would appear to be of little value in helping select documents that are excluded from the index vocabulary are called:

  1. Stop Words
  2. Tokens
  3. Lemmatized Words
  4. Stemmed Terms
  

Question 287 : The process of understanding the meaning and interpretation of words, signs and sentence structure is called as ________________.

  1. Tokenization
  2. Lexical Analysis
  3. Semanitc Analysis
  4. Sentiment Analysis
  

Question 288 : Which Of The Text Parsing Techniques Can Be Used For Noun Phrase Detection, Verb Phrase Detection, Subject Detection, And Object Detection In Nlp.

  1. Part Of Speech Tagging
  2. Skip Gram And N-Gram Extraction
  3. Continuous Bag Of Words
  4. Dependency Parsing And Constituency Parsing
  

Question 289 : What are the input and output of an NLP system?

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

Question 290 : " I promise to come" is which type of speech act?

  1. Commissives
  2. directives
  3. Declarations
  4. Representatives
  

Question 291 : Each connection in HMM represents a _______ over possible options; given our ______, this results in a large search space of the ________ of all words given the tag.

  1. Value, variables, associativity
  2. Distribution, tags, probability
  3. Variable, Labels, Transitivity
  4. Object, groups, associativity
  

Question 292 : Anaphoric relations hold between _______ phrases that refer to the same person or thing.

  1. Verb
  2. Noun
  3. Preposition
  4. Adjective
  

Question 293 : Speech Acts is defined as

  1. Using paralinguistic features when speaking
  2. The awareness of others' needs to be approved of and liked
  3. Communicative acts that carry meaning beyond the words and phrases used within them, for example, apologies and promises
  4. The reference of others is important
  

Question 294 : ____________________________ transfers linear sequences of words into structure.

  1. Semantic Analysis
  2. Tokens
  3. Lexical analysis
  4. Discourse
  

Question 295 : Parts-of-Speech tagging determines ___________

  1. part-of-speech for each word dynamically as per meaning of the sentence
  2. part-of-speech for each word dynamically as per sentence structure
  3. all part-of-speech for a specific word given as input
  4. all of the mentioned
  

Question 296 : "Sita loves her mother and Gita does too" contain which type of ambiguity?

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

Question 297 : 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 298 : In Sentiment analysis

  1. List the topics that a document deals with
  2. Assess the emotional content of a document
  3. Compress a document as much as possible without losing meaning, producing another document
  4. Given a question in natural language, provide an appropriate answer in natural language
  

Question 299 : ________is the problem of selecting a sense for a word from a set of predefined possibilities.

  1. Shallow Semantic Analysis
  2. Discourse
  3. Word Sense Disambiguation
  4. Pragmatic
  

Question 300 : Text summarization finds the most informative sentences in a ____;

  1. Video
  2. Image
  3. Sound
  4. Doccument