The I→OR and I→R;R→O rationale generator’s inputs:
explain cos_e question: [question] choice: [choice_0] choice: [choice_1] choice: [choice_2]
explain nli hypothesis: [hypothesis] premise: [premise].
The I→R;R→O pipeline label predictor’s input:
cos_e choice: [choice_0] choice: [choice_1] choice: [choice_2] explanation: [free-text rationale]
nli explanation: [free-text rationale]
The I→OR models’ outputs are trained and decoded as:
[label] explanation: [free-text rationale]

Table 8: T5 input-output formatting.

Dataset
E-SNLI
CoS-E v1.0
CoS-E v1.11

Random Majority-Vote
Accuracy
Accuracy
33.39
33.33
33.75
33.33
20.0
20.31
Measuring Association Between Labels and Free-Text Rationales