Generating Uncontextualized and Contextualized Questions for
  Document-Level Event Argument Extraction
Md Nayem Uddin Enfa Rose George Eduardo Blanco Steven Corman
This paper presents multiple question generation strategies for
document-level event argument extraction. These strategies do not require human
involvement and result in uncontextualized questions as well as contextualized
questions grounded on the event and document of interest. Experimental results
show that combining uncontextualized and contextualized questions is
beneficial, especially when event triggers and arguments appear in different
sentences. Our approach does not have corpus-specific components, in
particular, the question generation strategies transfer across corpora. We also
present a qualitative analysis of the most common errors made by our best
model.