Natural Language Processing · TEE · papers

Q1d · NLU versus NLG and applications

2025-02-21 · re-exam · recovered AI paper

Previous examination · complete worked answers

Question. Compare Natural Language Understanding and Natural Language Generation. List real-world NLP applications that use these concepts. [individual allocation not printed; Q1 totals 20]

Answer

Natural language understanding (NLU) maps language into an interpretation useful for a task: intents, entities, semantic relations or another meaning representation. Natural language generation (NLG) produces human-language output from data, a representation or another source.

“Book a ticket to Pune tomorrow.”
NLU: intent=book; destination=Pune; date=tomorrow
Application: search available journeys
NLG: “Here are the available journeys to Pune.”
FeatureNLUNLG
DirectionLanguage → interpretationData/representation → language
Main concernMeaning, intent, ambiguityContent choice, organization, fluent wording
ExampleFind destination in a requestWrite the booking confirmation
Common failureWrong destination or senseUnclear, unsupported or ungrammatical output

NLG stages in a classical pipeline

  1. Content determination: choose facts to communicate.
  2. Data interpretation: identify relationships or trends.
  3. Document planning: organize facts in a useful order.
  4. Sentence aggregation: combine related facts without repetition.
  5. Lexical and grammatical realization: choose words and construct grammatical sentences.
  6. Presentation: format the generated message for its audience.

For a weather report, facts {city=Pune, temperature=28°C, rain=yes} can become “Pune will have rain with a temperature of 28°C.” NLU would instead extract facts or intent from an incoming language message.

NLU = language se meaning andar. NLG = data se language bahar.

A question-answering assistant interprets intent/entities through NLU and composes an answer through NLG. Translation interprets source meaning and generates a target-language sequence. A customer-support system classifies requests and generates a contextual reply.