Learning Representation Mapping for Relation Detection in Knowledge Base Question Answering
Table 4: Seen relation prediction rate in the Test-unseen set. We calculate the macro average of this rate.
['Model', 'Seen Rate ↓ (%)']
Seen Relation Bias We use macro-average to calculate the percentage of instances whose relations are wrongly predicted to be a seen relation on Test-unseen. We call this indicator the seen rate, the lower the better. Because the seen relations are better learned after fine-tuning, while the representations for unseen relations are not updated well. So the relation detection model may have a strong trend to select those seen relations as the answer.