We implement and compare four types of neural models: 1) The previously described joint model from Section 3.4 (called Joint Model in the tables); 2) The same as 1), but without the fullyconnected input layers (called Joint Model No FC Input in the table); 3) The same as 1), but the model only predicts the link task, and is therefore not optimized for type prediction (called Single-Task Model in the table); 4) A non-sequence-tosequence model that uses the hidden layers produced by the BLSTM encoder with the same type of attention as the joint model (called Joint Model No Seq2Seq in the table).
d i in Equation 3 is replaced by e i .