Natural Language Processing MCQ

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Question 451 : Maximum Entropy Model combines which features and in which model?

  1. Homogeneous features, probabilistic framework
  2. Heterogeneous features, dynamic framework
  3. Homogeneous features, randomized framework
  4. Heterogeneous features, probabilistic framework
  

Question 452 : Subsequent reference to an already introduced entity; "referring back" (-->Paul's on the phone. I don't wanna talk to -->him.)

  1. Face
  2. Words
  3. Anaphora
  4. Cataphora
  

Question 453 : 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 454 : Focus on what the words conventionally mean, rather than on what an individual speaker might think they mean, or want them to mean, on a particular occasion; concerned with objective or general meaning and avoids trying to account for subjective or local meaning

  1. semantic features
  2. semantic analysis
  3. Semantic roles
  4. semantics
  

Question 455 : Consider the statement: "Ban on dancing on Governor's desk. " would be interpreted as:

  1. (Ban (on dancing)) (on Governor's desk)
  2. (Ban on ((dancing) on Governor's desk)
  3. (Ban (on dancing on Governor's desk))
  4. (Ban on (dancing ) on ((governor’s)) desk)
  

Question 456 : Which Application Of Nlp Captures And Outputs Factual Information Contained Within A Document?

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

Question 457 : The input/output of a NLP system cannot be:

  1. Sentence
  2. Speech
  3. 3D Model
  4. Document
  

Question 458 : Inferrables, discontinuos sets, generics are the three types of referents that complicate the _________ problem.

  1. Word sense disambiguation
  2. discourse
  3. reference resolution
  4. pragmatics
  

Question 459 : What Does The Phenomena That Operates At Discourse Level Include?

  1. Cohesion And Coherence
  2. Corrosion And Erosion
  3. Connection And Resolution
  4. Co-Ordination And Co-Operation
  

Question 460 : It is not type of text summarization

  1. Extraction based
  2. Abstraction based
  3. Predicted based
  4. Information based
  

Question 461 : ___________ tools allow businesses to identify customer sentiment toward products, brands or services in online feedback.

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

Question 462 : ‘The Indian Soldiers fought like a Lion’, in order to understand the real meaning the statement has to undergo

  1. Semantic Analysis
  2. Pragmatic Analysis
  3. Discourse Analysis
  4. Syntactic Analysis
  

Question 463 : How many bi-grams can be generated from given sentence:“Analytics Vidhya is a great source to learn data science”

  1. 7
  2. 8
  3. 9
  4. 10
  

Question 464 : Which would definitely be rejected by the English syntactic analyzer?

  1. Rahul is going to school
  2. Rahul is Coming from School
  3. Rahul is in the school
  4. The Rahul the go to the school
  

Question 465 : 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 466 : 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. Classification
  

Question 467 : Lappin and Leass Algorithm is used for

  1. Coherence Relation
  2. Pronoun Resolution
  3. Anaphora Resolution
  4. Syntax Analysis
  

Question 468 : The __________________ summarization technique involves pulling keyphrases from the source document.

  1. Extractive
  2. Abstractive
  3. Regular
  4. Automatic
  

Question 469 : Semantic Analysis Is Concerned With

  1. Meaning Representation Of Linguistic Inputs
  2. Antonyms Of Linguistic Inputs
  3. Syntax Representation Of Linguistic Inputs
  4. Meaning Representation Of Programming Language Inputs
  

Question 470 : 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. every thing mentioned above
  

Question 471 : Google Translate is one of the ________________ application.

  1. Machine translation
  2. Information Retrieval
  3. Information Extraction
  4. Summarisation
  

Question 472 : Techniques not used in phrases extraction

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

Question 473 : Morphological Segmentation is ......

  1. Finding the sense of each word in the sentence
  2. Separating words into individual morphemes and identifyng the class of the morphemes
  3. An extension of propositional logic
  4. Separating words into individual tokens and counting its frequency of occurence
  

Question 474 : Which method of sentiment analysis uses a variety of words annotated by polarity score, to decide the general assessment score of a given content.

  1. Word-Based
  2. Lexicon-Based
  3. Hybrid
  4. Opinion-Based
  

Question 475 : Syntactic n -grams are n -grams defined by paths in ________ dependency or constituent trees rather than the linear structure of the text

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

Question 476 : "Car is a ______ of "vehical".

  1. Antonym
  2. Hypernym
  3. Hypernym
  4. Hyponym
  

Question 477 : Sentiment analysis is also known as ____

  1. Opinion mining
  2. Data mining
  3. Text Analysis
  4. Automatic Summerization
  

Question 478 : A grammar that produces more than one parse tree for the same sentence is called as _______

  1. Contiguous
  2. Ambiguous
  3. Unambiguous
  4. Regular
  

Question 479 : For Hate Speech Detection from facebook messages __________NLP technique can be used.

  1. Text Classification
  2. Information Retrieval
  3. Information Summairzation
  4. Information Indexing
  

Question 480 : The statement "Indirect speech acts are when there is no coincidence between the type of illocutionary act and the syntactic structure of the message", means that:

  1. The intention is not explicitly expressed in the message
  2. The intention is expressed in the message
  3. The act is expressed in intention
  4. The intention is expressed as the act.
  

Question 481 : Mentions are span of text referring to some entity. Which is not a mention here?

  1. Named entities
  2. Pronouns
  3. Noun phrases
  4. Adverb phrases
  

Question 482 : Polysemy is a Greek word, which means

  1. Many names
  2. Many signs
  3. Many meanings
  4. Many verbs
  

Question 483 : Mlmenu, A Natural Language Interface For The Ti Explorer, Is Similar To:

  1. Ethernet
  2. Naturallink
  3. Prolog
  4. The Personal Consultant
  

Question 484 : 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 485 : 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 486 : which model is used for statistical machine translation

  1. Probabilistic model
  2. Entropy model
  3. FST
  4. Rule based model
  

Question 487 : What Is Viewed As Problem Of Probabilistic Inference?

  1. Speech Recognition
  2. Speaking
  3. Hearing
  4. Utterance
  

Question 488 : NP → Det Adj Noun, it denotes ____

  1. Adjective Phrase
  2. Noun Phrase
  3. Noun Adjective Phrase
  4. Determiner Phrase
  

Question 489 : A prepositional phrase consists of a preposition and its

  1. Object
  2. Subject
  3. Noun
  4. Verb
  

Question 490 : Which algorithm is used to train HMM model?

  1. Early algorithm
  2. Lexk algorithm
  3. Forward-backward or Welch algorithm
  4. A centering algorithm
  

Question 491 : What is full form of NLP?

  1. Natural Language Processing
  2. Natural Language Procedure
  3. Natural Language Process
  4. Natural Language pages
  

Question 492 : Which is concerned with retrieval from a document collection where documents in multiple languages co-exist and need to be retrieved to a query in any language.

  1. CLIR
  2. BLIR
  3. MLIR
  4. Monolingual IR
  

Question 493 : which type of summarizer will be suitable for summarizing tweets about Covid19 ?

  1. Extractive
  2. Explorative
  3. Explanable
  4. Absolute
  

Question 494 : Tool, instrument, implement, organ, utensil ---is example of ______

  1. Homonym
  2. Antonym
  3. Hyponymy
  4. Synonymy
  

Question 495 : ___________ tagger uses probabilistic and statistical information to assign tags to words.

  1. Rule based
  2. Stochastic tagger
  3. Statistical Tagger
  4. POS tagger
  

Question 496 : Over-stemming can also be regarded as __________________.

  1. False-Positives
  2. False-Negative
  3. True-Positive
  4. True-Negative
  

Question 497 : Following property is of - .These taggers are knowledge-driven

  1. Rule based Tagging
  2. Stochastic Tagging
  3. Rule based Tagging and Stochastic Tagging
  4. Neither Rule based Tagging nor Stochastic Tagging
  

Question 498 : Which of the following is the example of surface segmentation?

  1. Achievability = achievabil + ity
  2. Achievability = achiev + ability
  3. Achievability = Achieve + able + ity
  4. Achievability = achiev + abil + ity
  

Question 499 : In text mining, how the words ‘lovely’ is converted to ‘love’-

  1. By stemming
  2. By tokenization
  3. By lemmatization
  4. By rooting
  

Question 500 : It performs extensive analysis of linguistic phenomena through explicit representation of facts about language and well-understood knowledge representation schemas and associated algorithms. What is it?

  1. Convolutional Neural Networks
  2. Rule based Approach
  3. Corpus based.
  4. Hybrid