I am reading the paper of "Reasoning With Neural Tensor Networks for Knowledge Base Completion". I read it many times but I couldn't understand the parameters that are used especially the parameter U. they say that is one of the standard parameters of a basic neural net. I didn't get that, did I miss something or what?
I think you shouldn't read into it too much. It's simply a dot product between relation specific weights and the entity pair embedding. You can also think of $U$ as being the sole parameters in the last layer of the network which has no activation, no bias, and one output.