… Most previous approaches typically view event detection as a triggerbased … to event detection
by formulating it as a graph parsing problem, which can explicitly model the multiple event …

… event triggers and arguments as nodes in a semantic graph. Event extraction therefore becomes
a graph parsing … performing event detection and argument extraction jointly; 2) detecting …

… formulate the event extraction task as graph parsing, which … First, this graph parsing
formulation can naturally model the … event detection performance; (2) more importantly, our graph …

… dual relational graph for event detection, we propose an augmented relational graph attention
… with Biaffine parser achieves better performance in event detection since the dependency …

… graphs is surrounded by its direct syntactic governor and dependent words (the neighbors),
… volution over dependency graphs for ED in this paper. The dependency parse tree for the …

… nested and flat event structures. We explore a rich feature space that models both the events
to be parsed and context from … We create edges in the graph in the following way. For each …

… for entity/event detection, it cannot identify overlapping entities/event triggers. Furthermore,
the approach relies on syntactic information from an external parser and focuses only on …

… event triggers and classifying them into specific types. In this paper, we focus on the event
detection task … In this work, all AMR parse graphs are automatically generated from the first pub…

… We attribute the performance gain to two aspects: (1) Compared with the other
dependency-parsing-based event detection models, we do not use a full range of parsing labels, …

… graph of trigger-argument structures. Unlike existing structured prediction tasks such as …
parsing, the task targets to detect DAG structures, which constitute events, from the relation graph…