Process / pipeline

Natural Language Generation — Data-to-Text

Natural Language Generation (NLG) is the branch of natural language processing that automatically produces fluent, human-readable text from structured data, knowledge graphs, or semantic representations. Formalised in the classical pipeline by Reiter and Dale (2000) and surveyed comprehensively by Gatt and Krahmer (2018), NLG powers applications ranging from automated financial reporting and weather bulletins to data storytelling and conversational agents.

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Sources

  1. Gatt, A. & Krahmer, E. (2018). Survey of the State of the Art in Natural Language Generation: Core Tasks, Applications and Evaluation. Journal of Artificial Intelligence Research, 61, 65-170. link
  2. Reiter, E. & Dale, R. (2000). Building Natural Language Generation Systems. Cambridge University Press. ISBN: 9780521620369

Related methods

Referenced by

ScholarGateNatural Language Generation (Natural Language Generation (NLG)). Retrieved 2026-06-04 from https://scholargate.app/en/text-mining/natural-language-generation