Identifying Cross-Document Relations between Sentences

A pair of sentences in different newspaper articles on an event can have one of several relations. Of these, we have focused on two, i.e., equivalence and transition. Equivalence is the relation between two sentences that have the same information on an event. Transition is the relation between two sentences that have the same information except for values of numeric attributes. We propose methods of identifying these relations. We first split a dataset consisting of pairs of sentences into clusters according to their similarities, and then construct a classifier for each cluster to identify equivalence relations. We also adopt a “coarse-to-fine” approach. We further propose using the identified equivalence relations to address the task of identifying transition relations.