Hi, I like your paper so i read your released code. Then the following confusion comes to me. The adjacencies is put forward into the training process to represent the graph structure, and the v in adjacencies is obtained solely from train_batcher['rel']. It seens that the 'rel_reserve' is excluded in the training process. But in evaluation, the (e2, rel_reverse, adjacencies) is put forward into the model. I am confused, if the model doesn't see the 'rel_reverse' in the training then how could it handle the 'rel_reverse' in evaluation? Looking forward to hearing from you soon. Best wise.
Hi, I like your paper so i read your released code. Then the following confusion comes to me. The adjacencies is put forward into the training process to represent the graph structure, and the v in adjacencies is obtained solely from train_batcher['rel']. It seens that the 'rel_reserve' is excluded in the training process. But in evaluation, the (e2, rel_reverse, adjacencies) is put forward into the model. I am confused, if the model doesn't see the 'rel_reverse' in the training then how could it handle the 'rel_reverse' in evaluation? Looking forward to hearing from you soon. Best wise.