For a probability assignment $P$ on a finite set $X$ of variables, a source query $q$, a $\mathcal{B}[X]$-instance $\hat I$ and a tuple $t$, the marginal probability that $t$ appears in the answer of $q$ on a random world of $\hat I$ equals the probability of the annotation of $t$ in the annotated answer $\langle\!\langle q \rangle\!\rangle_{\hat I}$: $\Pr(t \in q(\hat I)) = \Pr\big(\bigvee_{(t, \alpha) \in \langle\!\langle q \rangle\!\rangle_{\hat I}} \alpha\big)$. This is the paper's Theorem 12, the justification of intensional probabilistic query evaluation: evaluate the query once over Boolean-function annotations and take the probability of the resulting function.