# Q1A · NLU and NLG

Subject: Natural Language Processing

Exam: TEE

Reader: https://deep-learning-study-room.vercel.app/nlp/#tee/papers/final-2025/final-2025-q1a

Canonical: https://deep-learning-study-room.vercel.app/read/nlp/tee/papers/final-2025--final-2025-q1a/

Actual final examination · 2 December 2025 · 100 marks · 3 hours

Question. Differentiate between Natural Language Understanding (NLU) and Natural Language Generation (NLG) in NLP with suitable examples. [5 marks]

### Answer

**Natural Language Understanding (NLU)** interprets language to identify its meaning, intent and relevant information. **Natural Language Generation (NLG)** produces language that expresses information in a useful form.

| Basis | NLU | NLG |
| --- | --- | --- |
| Direction | Language → meaning or structured information | Meaning or structured information → language |
| Typical input | A user utterance, document or sentence | Facts, a database record, a prompt or a representation |
| Typical output | Intent, entities, sentiment or a semantic representation | A sentence, explanation, summary or dialogue response |
| Main difficulty | Resolving ambiguity and context | Choosing accurate content and producing coherent, fluent wording |

### Example: a weather assistant

User: “Will it rain in Mumbai tomorrow?” NLU recognises a weather-query intent, the location Mumbai and the date tomorrow. After a weather service supplies the forecast, NLG produces “Rain is likely in Mumbai tomorrow; carry an umbrella.”

User language → NLU: identify request → Retrieve forecast → NLG: express answer

The two functions often work together in a chatbot. Understanding the request and wording the reply are separate tasks; fluent generation alone does not prove correct understanding.

**Yaad rakho:** NLU mein meaning nikalo; NLG mein meaning ko sentence banao.