Joint Event and Temporal Relation Extraction with Shared Representations and Structured Prediction

The task can be modeled as building a graph for a given text, whose nodes represent events and edges are labeled with temporal relations correspondingly. Figure 1a illustrates such a graph for the text shown therein. The nodes assassination, slaughtered, rampage, war, and Hutu are the candidate events, and different types of edges specify different temporal relations between them: assassination is BEFORE rampage, rampage INCLUDES slaughtered, and the relation between slaughtered and war is VAGUE. Since "Hutu" is actually not an event, a system is expected to annotate the relations between "Hutu" and all other nodes in the graph as NONE (i.e., no relation). As far as we know, all existing systems treat this task as a pipeline of two separate subtasks, (a) Temporal Relation Graph (b) Pipeline Model (c) Structured Joint Model Figure 1: An illustration of event and relation models in our proposed joint framework.