Practice Named Entity Recognition (ner) (9.2.3) - Natural Language Processing (NLP)

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9 questions

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Exercise
6 questions · about 4 min · pass mark 70%. Hints available.
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Quiz
3 questions · about 2 min · pass mark 70%. Hints available.
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6 sample questions

Question 1.
What does NER stand for?
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Look for the acronym in the term.
Question 2.
Name a type of entity recognized by NER.
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Think of names or specific data points commonly found in texts.
3Question 3.
What is the primary function of Named Entity Recognition?
- Translate text
- Identify and classify named entities
- Generate text
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Focus on what the title suggests.
4Question 4.
True or False: NER only identifies organizations and locations.
- True
- False
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Think about all the types mentioned.
Question 5.
Given a piece of text, conduct an NER analysis to extract and classify all named entities. Discuss the methodology used.
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Outline the usage of NER tools.
Question 6.
Evaluate the potential ethical implications of using NER in sensitive sectors like healthcare or legal systems.
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Consider potential biases in data processing and the responsible usage of extracted information.

5 more questions in this section. Enroll free to practise them all.