Our idea is to train a neural network to solve the analogy problem between any two entity pairs in this dataset, as long as they are described by the textual contexts where they co-occur.
this task is reduced to a binary classification of determining whether the relational similarity between the representations of two sets of mentions exceeds a threshold.