NLP MCQ Quiz

  1. NLP stands for Natural Language Processing.
  2. NLP is concerned with the interactions between computers and human (natural) languages.
  3. The following areas where NLP can be useful -
  4. Machine Translation is that converts -
  5. Which of the following is the field of Natural Language Processing (NLP)?
  6. What is Natural Language Processing good for?
  7. You can build a machine learning RSS reader in less than 30-minutes using -
  8. Natural Language Processing (NLP) is the field of
  9. NLP is concerned with the interactions between computers and human (natural) languages.
  10. One of the main challenge/s of NLP Is _________________ .
  11. Choose form the following areas where NLP can be useful.
  12. Coreference Resolution is -
  13. Morphological Segmentation
  14. In linguistic morphology, _____________ is the process for reducing inflected words to their root form.
NLP MCQ

Take NLP MCQ Quiz & Online Test to Test Your Knowledge

Practice below the best NLP MCQ Questions test that checks your basic knowledge of NLP (Natural Language Processing). This NLP MCQ Test contains 25+ NLP Multiple Choice Questions. You have to select the right answer to every question to check your final preparation for your interview. apart from this, you can download the NLP MCQ PDF below completely free.

  • true
  • false
  • Automatic Text Summarization
  • Information Retrieval
  • Automatic Question-Answering Systems
  • All of the Above
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  • Human language to machine language
  • One human language to another
  • Any human language to English
  • Machine language to human language
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  • Computer Science
  • Artificial Intelligence
  • Computational linguistics
  • All of the above
Download Free : NLP MCQ PDF
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  • Summarize blocks of text
  • Automatically generate keyword tags
  • Identify the type of entity extracted
  • All of the above
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  • ScrapeRSS
  • Html2Text & AutoTag
  • Sentiment Analysis
  • All of the mentioned
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  • Artificial Intelligence
  • Computer Science
  • Linguistics
  • All of the above
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  • Handling Tokenization
  • Handling Ambiguity of Sentences
  • Handling POS-Tagging
  • All of the above
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  • Automatic Text Summarization
  • Automatic Question-Answering Systems
  • Information Retrieval
  • All of the above
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  • Anaphora Resolution
  • Given a sentence or larger chunk of text, determine which words (“mentions”) refer to the same objects (“entities”)
  • Both a & b
  • None of the above
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  • Is an extension of propositional logic
  • Does Discourse Analysis
  • Separate words into individual morphemes and identify the class of the morphemes
  • None of the mentioned
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  • spatial base
  • danger zone
  • environment
  • work envelop
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  • Hill-climbing search
  • Planning algorithm
  • Graphplan
  • None of the above
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  • symbolic and numeric
  • algorithmic and heuristic
  • time and motion
  • understanding and generation
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  • 3rd Generation language
  • 4th Generation language
  • 5th Generation language
  • 6th Generation language
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  • dividing up a text into individual words in English.
  • understanding the context in which something is said.
  • recognizing typographical or grammatical errors in texts
  • distinguishing between words that have more than one meaning.
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  • text mining
  • artificial intelligence
  • computational linguistics
  • All of the above
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  • Handling Tokenization
  • Handling POS-Tagging
  • Handling Ambiguity of Sentences
  • None of the above
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