Algorithm 1 Learning Algorithm of ListNet method (cited from the paper of (Cao et al., 2007)) Input: Set of training instances: Parameter: iteration number T and learning rate η Initialize parameter ω for t = 1 → T do for i = 1 → m do Input x (i) to Neural Network and Compute score list Compute gradient ∆ω using equation 3Update ω = ω − η × ∆ω end for end for Output: Neural Network model ω ∆ω is computed using the following formula: (3) In previous models, they only determine how good a candidate antecedent is relative to the anaphoric NP, but not how good a candidate antecedent is relative to other candidates.
they fail to answer the question of which candidate antecedent is the most probable.