Practice Named Entity Recognition (ner) (27.3.3) - Concepts of Natural Language Processing (NLP)
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Named Entity Recognition (NER)

Practice - Named Entity Recognition (NER)

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Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What does NER stand for?

💡 Hint: Think about the meaning of each word in the acronym.

Question 2 Easy

Give an example of an entity that NER might identify.

💡 Hint: Consider common nouns you encounter.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is the primary goal of Named Entity Recognition?

To translate languages
To classify names in text
To analyze sentiment

💡 Hint: Think about what NER stands for.

Question 2

True or False: NER can misclassify terms based on context.

True
False

💡 Hint: Reflect on examples like 'bat.'

1 more question available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Design a scenario where NER could fail and explain how this could impact data analysis.

💡 Hint: Consider the language diversity in informal communication.

Challenge 2 Hard

Create a mini-project that implements NER on a specific dataset, ensuring to handle ambiguous terms. Describe your approach.

💡 Hint: Think of model enhancements or extra training data.

Get performance evaluation

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