Improving event co-reference by context extraction and dynamic feature weighting

Event co-reference is the process of identifying descriptions of the same event across sentences, documents, or structured databases. Existing event co-reference work focuses on sentence similarity models or feature based similarity models requiring slot filling. This work shows the effectiveness of using a hybrid approach where the similarity of two events is determined by a combination of the similarity of the two event descriptions, in addition to the similarity of the event context features of location and time. A dynamic weighting approach is taken to combine the three similarity scores together. The described approach provides several benefits including improving event resolution and requiring less reliance on sophisticated natural language processing.