Looking at figure 2, it is not clear to me exactly what kind of
structures the hill-climbing algorithm is constructing. I understand
they are only part of the learned structures, but

a) They seem too "specialized" to work for other kinds of announcements:
the training and testing sets are all from a single university.

b) If the algorithm was trained in a less restricted environment
where larger structures are needed (for example, hundreds of
different hall names, thousands of numbers), would the algorithm
be able to properly learn the corresponding structures? Or would it
be too computationally expensive to do hill climbing?

Since there is structure in the seminar announcements, then the learned
structures should be concise and understandable. But if the learned
structures grow indiscriminately as the variety of test cases grows,
then I would not be sure whether this approach is correct.