In local search, we have to deal with a problem central to many knowledge driven products: reasoning about diverse and often conflicting records intended to denote some real world entities (in this case local businesses and other concepts). This problem is common in other domains including commerce (online shopping).
We are currently looking around for a new laptop and one of the first results I found on Amazon has the following product information:
I assume that the 'product features' are free form text provided by someone and that the list of key value pairs represents Amazon's schema for computers. With fixed schema, it is worthwhile building deep expertise in parsers that can recognize (denotations of) concepts that can populate that schema. For example, in local search this core competency might be in parsing addresses.
I have no reason to believe that Amazon's devs can't handle this, and more than likely what we are seeing is simply a reflection of a resource bound cut-line for feature work (i.e. the task of solving this problem simply wasn't funded). But it is a nice illustration of where NLP can fit in to and improve a real product.