Python Quiz for NLP – 03

Introduction

Delving into the realm of Natural Language Processing (NLP) opens up a fascinating frontier of possibilities. Our Python Quiz for NLP is designed to challenge your knowledge, provide insights, and add a fun twist to your learning journey. Through a series of curated questions, you’ll explore various NLP concepts and Python implementations, growing your comprehension and confidence in handling real-world language processing tasks. Natural Language Processing (NLP) is a field at the intersection of computer science, artificial intelligence, and linguistics. Its goal is to enable computers to understand, interpret, and generate human language in a valuable way.

So, are you ready to put your NLP skills to the test?

Read to prepare: Interview-questions-natural-language-processing-using-python

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Python NLP – 03

Level: Advanced

1 / 10

1. Which function in NLTK is commonly used for named entity recognition?

a) nltk.sent_tokenize()

b) nltk.pos_tag()

c) nltk.word_tokenize()

d) nltk.ne_chunk()

2 / 10

2. How do you get the type of named entities using spaCy?

a) Using `ent.text` for each `ent` in `doc.ents`.

b) Using `doc.tokens`.

c) Using `doc.sentiment`.

d) Using `ent.label_` for each `ent` in `doc.ents`.

3 / 10

3. What does the following code do in NLP? `nltk.word_tokenize(“Hello, World!”)`

a) It tokenizes the sentence into words.

b) It translates the sentence into another language.

c) It removes stop words from the sentence.

d) It performs sentiment analysis.

4 / 10

4. What does the following code do? `doc = nlp(“Steve Jobs founded Apple.”); [ent.text for ent in doc.ents]`

a) Tokenizes the text into words.

b) Translates the text into another language.

c) Performs sentiment analysis on the text.

d) Extracts named entities from the text.

5 / 10

5. Which Python library is commonly used for Named Entity Recognition?

a) Pandas

b) Matplotlib

c) NumPy

d) spacy

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6. What is the purpose of word embeddings in NLP?

a) To tokenize sentences.

b) To convert words into numerical vectors.

c) To perform arithmetic operations.

d) To check the spelling of words.

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7. Which Java library is often used for named entity recognition and can be integrated with Python?

a) Beautiful Soup

b) Jupyter

c) Stanford NER

d) Scikit-learn

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8. Which spaCy model is generally used for English text entity recognition?

a) fr_core_news_sm

b) es_core_news_sm

c) en_core_web_sm

d) de_core_news_sm

9 / 10

9. Which of the following is a common output of sentiment analysis?

a) A list of tokens

b) True or False

c) Positive, Negative, or Neutral

d) An array of numbers

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10. What does TF-IDF stand for in the context of NLP?

a) Text Frequency-Index Document Frequency

b) Token Frequency-Indexed Document Frequency

c) Time Frequency-Inverse Document Frequency

d) Term Frequency-Inverse Document Frequency

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