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When reading a literary piece, readers often make inferences about variouscharacters' roles, personalities, relationships, intents, actions, etc. Whilehumans can readily draw upon their past experiences to build such acharacter-centric view of the narrative, understanding characters in narrativescan be a challenging task for machines. To encourage research in this field ofcharacter-centric narrative understanding, we present LiSCU -- a new dataset ofliterary pieces and their summaries paired with descriptions of characters thatappear in them. We also introduce two new tasks on LiSCU: CharacterIdentification and Character Description Generation. Our experiments withseveral pre-trained language models adapted for these tasks demonstrate thatthere is a need for better models of narrative comprehension.

"Let Your Characters Tell Their Story": A Dataset for Character-Centric Narrative Understanding