I thought one of their main points in the paper is that there are always going to be more data sets in "natural" form than in conveniently marked-up form, so that a researcher has to develop tools to deal with natural data as they are and still cope with that. Then the next new-and-improved scheme for semantic mark-up can learn from what is observed in vast data sets.
