Grade VIII • Artificial Intelligence

NLP – Short Answer Questions

NLP Tasks & Techniques • Sentiment Analysis • Lemmatization • Sentence Segmentation • NLG

Questions & Answers

1. What is Sentiment Analysis, and how is it useful in understanding text?

Answer:

Sentiment Analysis is an NLP technique used to identify the emotional tone or opinion expressed in text. It can classify text as positive, negative, neutral, or into more detailed sentiment categories.

It helps organisations understand people's opinions, preferences and reactions from sources such as reviews, surveys and social-media posts.

Example: A product review saying "The camera quality is excellent" would generally be identified as expressing a positive sentiment.

2. What is Lemmatization in NLP, and how does it work?

Answer:

Lemmatization is an NLP technique that reduces a word to its meaningful base or dictionary form, called its lemma.

It considers the word's context and grammatical role to determine the appropriate base form.

Examples:
running → run
better → good in contexts where better is the comparative form of good.

3. What is Sentence Segmentation, and when is it used in NLP?

Answer:

Sentence Segmentation, also called sentence boundary detection, is the process of dividing a block of text into individual sentences.

It is commonly used as an early step in NLP systems so that each sentence can be processed and analysed separately.

Example:
"Python is easy to learn. It is widely used."

becomes:
1. "Python is easy to learn."
2. "It is widely used."

4. Mention any two real-life applications where NLP is commonly used.

Answer:

Two common real-life applications of NLP are:

  1. Voice Assistants: NLP helps systems understand and respond to spoken or written user requests.
  2. Machine Translation: NLP is used to translate text from one language into another.
Other examples: Chatbots, spam detection, search engines, text summarisation, sentiment analysis and predictive text.

5. What does NLG stand for in the context of NLP, and what is its function?

Answer:

NLG stands for Natural Language Generation. It is a part of NLP concerned with generating human-readable language from structured data, information or other representations.

NLG can be used to produce text such as summaries, reports, explanations and responses.

Example: A system can analyse weather data and generate a sentence such as "Heavy rain is expected in the afternoon."

Quick Revision

NLP Concept Key Point
Sentiment Analysis Identifies the sentiment or emotional tone expressed in text.
Lemmatization Converts words to their meaningful dictionary or base forms.
Sentence Segmentation Divides a document or text into individual sentences.
NLP Applications Include voice assistants, translation, chatbots, search and text analysis.
NLG Generates natural-language text from data or other structured representations.

Examples of NLP Tasks

Task Purpose Example
Sentence Segmentation Finds sentence boundaries. Splitting a paragraph into individual sentences.
Tokenization Breaks text into smaller units such as words or tokens. "NLP is useful" → NLP, is, useful
Lemmatization Finds the meaningful base form of a word. studies → study
Sentiment Analysis Determines sentiment expressed in text. Positive, negative or neutral review.
Machine Translation Converts text between languages. English → Hindi
NLG Generates natural-language text. Creating a written summary from data.

Key Terms

NLP: Natural Language Processing, a field of AI concerned with enabling computers to process and work with human language.

Sentiment: The attitude, opinion or emotional tone expressed in text.

Lemma: The meaningful dictionary or base form of a word.

Segmentation: The process of dividing text into meaningful units, such as sentences.

NLG: Natural Language Generation, which produces natural-language text from data or other structured information.