Number of predictive classes you can find in text

From a discussion on the “Hutter-Prize” Google group:

…If A_1, A_2,… A_n are the contexts of A in some text, and X_1, X_2,…X_n are contexts of other tokens, then the number of ways A can have common contexts with other tokens in the text, and thus uniquely specify some new paradigmatic class, are just Matt’s “(n choose k) = n!/(k!(n-k)!) possible sets”, where k is the number of common contexts between A and some other token.

The syntagmatic distribution of sequences AX_? specified by these classes in the text can be random, because many different paradigmatic distributions (A_i,…A_i+k) can be equally likely (and must be, because many of the “n choose k” possible classes will overlap, and thus form complementary distributions with each other??) But the relationship between any given syntax and its corresponding paradigmatic distribution is not random. And the different paradigmatic distributions (knowledge?) governing that random syntax are not random either, just very numerous. Much more numerous than the sequence of 2n or so tokens needed to specify them.