I heard a story on NPR while driving today that referenced a recent Financial Times story about the use of natural language generation technology for producing financial stories. The financial company, Thomson, is now generating some of its stories using NLG. The NLG technology, based on the little bit of information I gathered from the NPR story and reading the associated article, seems to be straightforward template filling. This is not terribly surprising, given the stagnant nature of financial articles (grab any such article from WSJ and you see things like "The DOW went up ____ percent (___ points) because of ___." Most of this can be easily gathered from databases.
One might suspect that the final "___" (the reason) would be hard to come up with automatically, but apparently this is highly standardized as well. According to the NPR story following the one on the NLG technology, the number of reasons that fill that blank is nearly closed class ("profits" or "middle east" or "terrorism" or "bin Laden videotape" or "strong trading" or ...). And, based on some hear-say evidence, the reasons are largely bogus anyway (this is not surprising: summarizing one billion trades as being driven by a bin Laden videotape is highly suspect).
An amusing comment was made when the journalist at NPR asked the Thomson rep if his job was in danger. The response was that it was, only if he believed that his abilities topped out at filling out templates.
Anyway, if anyone knows more about the technology, and if there's anything interesting in it, it would be fun to know. Beyond that, I just thought it was fun that NLP technology made a spot on NPR.