"Let Your Characters Tell Their Story": A Dataset for Character-Centric Narrative Understanding
"Let Your Characters Tell Their Story": A Dataset for Character-Centric Narrative Understanding
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DOI：
10.18653/v1/2021.findings-emnlp.150
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发表时间：
2021-09
期刊：
影响因子：
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通讯作者：
Faeze Brahman;Meng Huang-;Oyvind Tafjord;Chao Zhao;Mrinmaya Sachan;Snigdha Chaturvedi
中科院分区：
文献类型：
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作者：
Faeze Brahman;Meng Huang-;Oyvind Tafjord;Chao Zhao;Mrinmaya Sachan;Snigdha Chaturvedi
当阅读文学作品时，读者经常对各种角色的角色、个性、关系、意图、动作等进行推断。虽然人类可以很容易地利用他们过去的经验来构建这种以角色为中心的叙事视图，但理解叙事中的角色对机器来说可能是一项具有挑战性的任务。为了鼓励在以人物为中心的叙事理解这一领域的研究，我们提出了LiSCU -一个新的文学作品及其摘要数据集，并与其中出现的人物描述配对。我们还介绍了两个新的LiSCU任务：字符识别和字符描述生成。我们的实验与几个预先训练的语言模型适用于这些任务表明，有必要更好的模型的叙事理解。
When reading a literary piece, readers often make inferences about various characters' roles, personalities, relationships, intents, actions, etc. While humans can readily draw upon their past experiences to build such a character-centric view of the narrative, understanding characters in narratives can be a challenging task for machines. To encourage research in this field of character-centric narrative understanding, we present LiSCU -- a new dataset of literary pieces and their summaries paired with descriptions of characters that appear in them. We also introduce two new tasks on LiSCU: Character Identification and Character Description Generation. Our experiments with several pre-trained language models adapted for these tasks demonstrate that there is a need for better models of narrative comprehension.