As a PhD graduate in NLG I wouldn't say NLG is a "young" research field. For example the oldest NLG book I have is Eduard Hovy's PhD work on the PAULINE system

As a PhD graduate in NLG I wouldn't say NLG is a "young" research field. For example the oldest NLG book I have is Eduard Hovy's PhD work on the PAULINE system ("Generating Natural Language Under Pragmatic Constraints"), which was published back 1988. The seminal reference book for NLG ("Building Natural Language Generation Systems") was published back in 2000. What's made NLG more interesting recently is that the computing environment has changed considerably. We have considerably more larger pools of time-series data than was available in the past and that we now also have standardised data-to-text pipeline architecture when creating NLG applications for such data. Nevertheless, I do agree there's still considerable challenges when trying to perform text-to-text generation which involves trying to combine NLP and NLG together to abstract, interpret, and then summarise unstructured free text.