Recent years have seen a gradual shift of focus from entity-based tasks to event-based tasks
in information extraction research. Being a core event-based task, event coreference …

Besides entity-centric knowledge, usually organized as Knowledge Graph (KG), events are
also an essential kind of knowledge in the world, which trigger the spring up of event-centric …

Despite recent promising results on the application of span-based models for event
reference interpretation, there is a lack of understanding of what has been improved. We …

While joint models have been developed for many NLP tasks, the vast majority of event
coreference resolvers, including the top-performing resolvers competing in the recent TAC …

We address two key challenges in end-to-end event coreference resolution research:(1) the
error propagation problem, where an event coreference resolver has to assume as input the …

Motivated by the recent successful application of span-based models to entity-based
information extraction tasks, we investigate span-based models for event coreference …

Multi-pass sieve approaches have been successfully applied to entity coreference resolution
and many other tasks in natural language processing (NLP), owing in part to the ease of …

The vast majority of existing work on learning-based event coreference resolution has
employed the so-called mentionpair model, which is a binary classifier that determines …

Events in text documents are interrelated in complex ways. In this paper, we study two types
of relation: Event Coreference and Event Sequencing. We show that the popular tree-like …

Event coreference resolution is the task of clustering event mentions that refer to the same
entity or situation in text and performing operations like linking, information completion, and …