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.

本文提出了多种问题生成策略，用于文档级事件论证提取。这些策略不需要人工参与，生成的问题既有非上下文化的问题，也有基于感兴趣事件和文档的上下文化问题。实验结果表明，将非上下文和上下文问题相结合是有益的，特别是当事件触发器和论证出现在不同的句子中。我们的方法没有特定于语料库的组件，具体而言，问题生成策略可以在不同的语料库中进行转移。我们还对我们最佳模型最常见的错误进行了定性分析。