Natural language generation (NLG) is a subfield of artificial intelligence (AI) in which computers use data to produce text, often called narratives. Some experts consider NLG a part of natural language processing (NLP). However, the two are really opposites. NLG uses data to generate text, and NLP extracts data from text or audio.

- Henry H. Eckerson in The Ultimate Guide to Natural Language Generation: Definitions, Trends, and Products

January 17, 2018 (Report)

Natural language generation software uses data input and a combination of templates, rules, and algorithms to generate text, known as narratives, that read as if a human wrote them. NLG tools enable users to automate writing tasks such as reports, financial news, and product descriptions, summarize and explain datasets and BI dashboards, and write mass personalized communications. To find out more about NLG, check out my recent report, The Ultimate Guide to Natural Language. NLG is considered a developing technology.

- Henry H. Eckerson in The Demise of the Keyboard – Natural Language Technology Takeover

March 21, 2018 (Blog)

NLG offerings ingest data and use a combination of templates, rules, and artificial intelligence technology to produce reports, summaries, product descriptions, analysis, and more in plain language. There are three overarching use cases for NLG: automation, BI and reporting, and personalization.

- Henry H. Eckerson in Do You Need Natural Language Generation?

January 10, 2018 (Blog)