Holistic pair-wise judgments help elicit imprecise information on trade-offs.

Selecting the best pair-wise comparison questions can be difficult.

We propose an entropy-based framework to select optimal elicitation questions.

The framework applies when attribute values have probability distributions.

We apply it to pair-wise elicitation and evaluate it using computational tests.