 Shannon's block-entropy approximations

In A Mathematical Theory of Communication by Claude Shannon, Claude Shannon compares block uncertainty per symbol, denoted $G_N$, with conditional uncertainty given the preceding symbols, denoted $F_N$. Theorems 5 and 6 connect both decreasing approximations to the source's limiting uncertainty. He uses symbol statistics at increasing block lengths to expose structure missed by single-letter counts.^[ref] The fair marginal bits of the binary Markov source provide a small exact example of that distinction.