I think you're essentially asking what's the probability of the state being $E_0$ if you get the "?" outcome. So let's work this out:
$$\operatorname{Pr}(E_0|\Pi_?) = \frac{\operatorname{Pr}(\Pi_?|E_0)\operatorname{Pr}(E_0)}{\operatorname{Pr}(\Pi_?)}
= \frac{\operatorname{Pr}(\Pi_?|E_0)\operatorname{Pr}(E_0)}{\operatorname{Pr}(\Pi_?|E_0)\operatorname{Pr}(E_0)+\operatorname{Pr}(\Pi_?|E_1)\operatorname{Pr}(E_1)}.$$
Assume unbiased priors: $\operatorname{Pr}(E_0)=\operatorname{Pr}(E_1)=1/2$.
You're asking about the scenario where $\operatorname{Pr}(\Pi_1|E_1)\equiv p_1\simeq 1$, which then also implies $\operatorname{Pr}(\Pi_?|E_1)= 1-p_1\simeq 0$. It would seem that plugging this in the above formula would give $\operatorname{Pr}(E_0|\Pi_?)\simeq 1$, and thus yes, in such a scenario, you'd conclude that the $\Pi_?$ outcome actually tells you quite a bit about the input state.
However, the issue in this reasoning is that an optimal discrimination strategy such that $\operatorname{Pr}(\Pi_1|E_1)\simeq 1$ corresponds to a scenario where the states to discriminate are orthogonal, and then also $\operatorname{Pr}(\Pi_0|E_0)\simeq 1$, and $\Pi_?$ is altogether observed with vanishing probability.
Another way to see this is that having $\Pi_?$ give you meaningful information violates the premise of the measurement being optimal for unambiguous state discrimination. If the $\Pi_?$ outcome tells you any amount of information about the input state, then there must be a better way to measure that makes use of this information.
In fact, the optimal unambiguous state discrimination strategy never gives you such a scenario. For unbiased priors, the success probabilities for the optimal strategy are equal: $p_0=p_1$ in your notation. More generally, for priors $\eta_i$, they satisfy $1-p_0=\sqrt{\eta_1/\eta_0}\cos\Theta$ and $1-p_1=\sqrt{\eta_0/\eta_1}\cos\Theta$ (using the notation of the pdf notes you linked previously). Notice that $\operatorname{Pr}(\Pi_?|E_i)=1-p_i$, and thus the formula above for $\operatorname{Pr}(E_0|\Pi_?)$ works out to
$$\operatorname{Pr}(E_0|\Pi_?)
= \frac{\eta_0 \sqrt{\eta_1/\eta_0}}{\eta_0\sqrt{\eta_1/\eta_0} + \eta_1\sqrt{\eta_0/\eta_1} } = \frac12,$$
which is exactly what we should expect from the optimal strategy: the $\Pi_?$ outcome gives no information whatsoever.