Three questions

[zulihit]

Thank you for your work and I have three questions:

1. Why do you use this method to calculate the initialization range? I didn't see the relevant introduction in your paper. What's the purpose of this method?

self.embedding_range = nn.Parameter( torch.Tensor([(self.gamma.item() + self.epsilon) / hidden_dim]),
requires_grad=False )

self.entity_embedding = nn.Parameter(torch.zeros(nentity, self.entity_dim)) nn.init.uniform_( tensor=self.entity_embedding, a=-self.embedding_range.item(), b=self.embedding_range.item() )

2. This range is also used when pluralizing relationships. Why can this be done？

phase_relation = relation/(self.embedding_range.item()/pi) re_relation = torch.cos(phase_relation) im_relation = torch.sin(phase_relation)

3. In the rotate model, the calculations of head batch and tail batch are different in sign, but in the paper i can't find the head-batch part, i can't understand this part

if mode == 'head-batch': re_score = re_relation * re_tail + im_relation * im_tail im_score = re_relation * im_tail - im_relation * re_tail re_score = re_score - re_head im_score = im_score - im_head else: re_score = re_head * re_relation - im_head * im_relation im_score = re_head * im_relation + im_head * re_relation re_score = re_score - re_tail im_score = im_score - im_tail