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MCQs

Total Questions : 20 | Page 1 of 2 pages
Question 1. What are the names of lecturers in this NLP part?
  1.    Stefan Kosztolanyi
  2.    Sebastian Poliak
  3.    Martin Smira
  4.    Both A & B
 Discuss Question
Answer: Option D. -> Both A & B
Question 2. Which of these are enghlish stopwords?
  1.    'i', 'me', 'my', 'myself'
  2.    'about', 'against', 'between', 'into'
  3.    'happy', 'sad', 'angry', ' 'amazing'
  4.    Both A & B
 Discuss Question
Answer: Option D. -> Both A & B
Question 3. Which are multiple word sequences?
  1.    Tokenization
  2.    Ngrams
  3.    Stopwords
  4.    Corpus
 Discuss Question
Answer: Option B. -> Ngrams
Question 4. What does NLP stand for? Write what the acronym means
  1.    Natural Language Processing
  2.    Nationwide Loan Processing
  3.    Netware Lite Protocol
  4.    None of these
 Discuss Question
Answer: Option A. -> Natural Language Processing
Question 5. Why we use named entity recognition in NLP?
  1.    Classify entities into predefined labels
  2.    Creating a set of vocabularies
  3.    Breaking sentences into words
  4.    None
 Discuss Question
Answer: Option A. -> Classify entities into predefined labels
Question 6. N-grams are defined as the combination of N keywords together
  1.    7
  2.    8
  3.    9
  4.    10
 Discuss Question
Answer: Option C. -> 9
Question 7. What is the field of Natural Language Processing (NLP)?
  1.    Computer Science
  2.    Artificial Intelligence
  3.    Linguistics
  4.    All of the mentioned
 Discuss Question
Answer: Option D. -> All of the mentioned
Question 8. Which of the following sense for the word “language” is not available in wordnet? i
  1.    3
  2.    5
  3.    4
  4.    None of these
 Discuss Question
Answer: Option C. -> 4
Question 9. ____________ is a Python library to make programs that work with natural language
  1.    NLTK
  2.    Pandas
  3.    Seaborn
  4.    BeautifulSoup
 Discuss Question
Answer: Option A. -> NLTK
Question 10. Tick whichever is an application Named Entity Recognition (NER)
  1.    Classifying content for NEWS providers
  2.    Efficient Search Algorithms
  3.    Analysis the rude behavior from customer feedback
  4.    All of above
 Discuss Question
Answer: Option D. -> All of above

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