Natural Language Processing MCQ
Question 751 : The bigram model approximates the probability of a word given all the previous words by using:
- The conditional probability of all the previous words
- The maximum likelihood estimation of the given word
- Only the conditional probability of the preceding word
- The maximum likelihood estimation of the preceding word
Question 752 : Consider the following corpus of 3 sentences. 1) I am here 2) who am I. 3) I would like to go. Calculate P(here|am) assuming a bi-gram language model.
- 02-03-2020 12:00:00 AM
- 01-02-2020 12:00:00 AM
- 01-03-2020 12:00:00 AM
Question 753 : “I went to the school, and they told me come on next day”. What type of ambiguity present in the given sentence?
- Syntactic ambiguity
- Anaphoric ambiguity
- Semantic ambiguity
- Lexical ambiguity
Question 754 : Which of the following is/are the input(s) to k-means algorithm?
- Number of clusters
- Class labels
- Distance metric
- Number of centroids
Question 755 : _________Reverses the antecedent-anaphora relationship by beginning with a pronoun, then later revealing more specific information
Question 756 : What are the possible input of an NLP system?
- Speech and noise
- Speech ,scan document and Written Text
- Noise and Written Text
- Noise and value
Question 757 : Capability vs Capabilities is an example of ______ morphology.
Question 758 : It is a process of generating a concise and meaningful summary of text from multiple text resources such as books, news articles,blog posts, research papers, emails, and tweets.
- Automatic Summerization
Question 759 : Spam email detection comes under which domain?
- Text Categorization
- Text Classification
- Sentiment Analysis
Question 760 : For e.g. "Before she purchased it, Mary checked warranty card of the product". In the context of pronoun, this is the example of
Question 761 : "The tour includes three Asian countries." Which is a noun phrase?
- The tour includes
- three Asian countries
- Three asian
- Tour includes
Question 762 : The Context Of A Word Provides Useful Information About Word Sense. Which Algorithms Can Be Braodly Classified Into Knowledge-Based And Corpus-Based Approaches
- Context-Based Disambiguation
- Context-Free Grammar
- Regular Expressions
- Context-Based Ambiguation
Question 763 : What type of relation exist between the words "meet" and "meat"?
Question 764 : What is Morphological Segmentation?
- Does Discourse Analysis
- Separate words into individual morphemes and identify the class of the morphemes
- Is an extension of propositional logic
- Separate sentences into individual morphemes and identify the class of the morphemes
Question 765 : Semantic model is not used for
- The meaning of words
- Knowledge about structure of discourse
- Common sense knowledge about the topic
- POS tag of word
Question 766 : In A Corpus Of N Documents, One Randomly Chosen Document Contains A Total Of T Terms And The Term “Hello” Appears K Times. What Is The Correct Value For The Product Of Tf (Term Frequency) And Idf (Inverse-Document-Frequency), If The Term “Hello” Appears In Approximately One-Third Of The Total Documents?
- Kt * Log(3)
- T * Log(3) / K
- K * Log(3) / T
- Log(3) / Kt
Question 767 : Which type of semantics is concerned with the linguistic study of systematic, meaning related structure of words or lexemes
- Compund Semantics
- Lexical semantics
- Compositional semantics
- Word Semantics
Question 768 : What is a difference between Finite State Automata (FSA) and Finite State Transducers (FST)?
- FSA contain single tape and FST also contain single tape.
- FSA contain single input tape and FST contain single output tape.
- FSA contain single input tape and FST contain input: output pair tapes.
- Both FSA and FST contains output tapes only.
Question 769 : Anita has got the transcripts for the Minster's press meet on NEP. She wants to summarize the Minister’s opinion on NEP strengths and weakness. Which of the following sumamrization methods should she apply?
- Abstractive generic
- Extractive generic
- Abstractive query focussed
- Summative generic
Question 770 : Maximum Entropy Markov Model (MEMM) used to handle______
- Unkonwn word
- Known word
- Multpile tag
- Single tag word
Question 771 : What is tokenization?
- Breaking sentences into words
- Creating a set of dictonories
- Removing repetation
- printing words
Question 772 : Humhe khaanna khaanna hai. Here the type of ambiguity is
Question 773 : Maximum Entropy Markov Models use a maximum entropy _______for _______ and local __________.
- Framework, Features, Normalization
- Rules, Variables, Classification
- Sets, Values, Distribution
- Rules, features, classification
Question 774 : How is the word "consultants" stemmed?