Asking It All: Generating Contextualized Questions for any Semantic Role

• URL: http://arxiv.org/abs/2109.04832v1
• Date: Fri, 10 Sep 2021 12:31:14 GMT
• Title: Asking It All: Generating Contextualized Questions for any Semantic Role
• Authors: Valentina Pyatkin, Paul Roit, Julian Michael, Reut Tsarfaty, Yoav Goldberg, Ido Dagan
• Abstract summary: We introduce the task of role question generation, which is given a predicate mention and a passage. We develop a two-stage model for this task, which first produces a context-independent question prototype for each role. Our evaluation demonstrates that we generate diverse and well-formed questions for a large, broad-coverage of predicates and roles.
• Score: 56.724302729493594
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

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