TellMeWhy: A Dataset for Answering Why-Questions in Narratives (2021)
Yash Kumar Lal, Nathanael Chambers, Raymond Mooney, Niranjan Balasubramanian
Answering questions about why characters perform certain actions is central to understanding and reasoning about narratives. Despite recent progress in QA, it is not clear if existing models have the ability to answer “why” questions that may require common-sense knowledge external to the input narrative. In this work, we introduceTellMeWhy, a new crowd-sourced dataset that consists of more than 30k questions and free-form answers concerning why characters in short narratives perform the actions described. For a third of this dataset, the answers are not present within the narrative. Given the limitations of automated evaluation for this task, we also present a systematized human evaluation interface for this dataset. Our evaluation of state-of-the-art models shows that they are far below human performance on answering such questions. They are especially worse on questions whose answers are external to the narrative, thus providing a challenge for future QAand narrative understanding research.
In Findings of ACL 2021, August 2021.

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Raymond J. Mooney Faculty mooney [at] cs utexas edu