Asking questions about a situation is an inherent step towards understanding it. To this end, we introduce the task of role question generation, which, given a predicate mention and a passage, requires producing a set of questions asking about all possible semantic roles of the predicate. We develop a two-stage model for this task, which first produces a context-independent question prototype for each role and then revises it to be contextually appropriate for the passage. Unlike most existing approaches to question generation, our approach does not require conditioning on existing answers in the text. Instead, we condition on the type of information to inquire about, regardless of whether the answer appears explicitly in the text, could be inferred from it, or should be sought elsewhere. Our evaluation demonstrates that we generate diverse and well-formed questions for a large, broad-coverage ontology of predicates and roles.

本文针对语境理解提出了角色提问生成任务，使用两阶段模型生成语境无关问题原型并通过修改使其符合语境。该方法不需要使用文本中的现有答案作为先决条件，而是基于所需询问的信息类型进行条件训练。评估结果表明，我们能够针对广泛覆盖的谓词和角色生成多样化和良好形式的问题。

问之所问：为任意语义角色生成情境化问题