Linguistic database summaries in the sense of Yager (1982), further extended to an implementable form by Kacprzyk & Yager (2001) and Kacprzyk, Yager & Zadrozny (2000), are extremely simple natural language like statements exemplified by, for a personnel database, “most employees are young and well paid” (with some degree of truth). They have been implemented in business contexts (cf. Kacprzyk & Zadrozny,????, Kacprzyk, Wilbik and Zadrozny, 2006–2008). An effective and efficient way of their generation was proposed by Kacprzyk & Zadrozny (????) by using an interactive procedure based on Kacprzyk & Zadrozny's (????) fuzzy database queries with linguistic quantifiers. Moreover, in Kacprzyk & Zadrozny (???) the role of Zadeh's (???) protoform was shown and their use advocated. Though linguistic database summaries have a strong resemblance to natural language generation (NLG), this issue was never considered. In this paper we indicate some important issues that are common to linguistic database summarization and natural language generation, and propose some possible research directions.