CHIRON: Rich Character Representations in Long-Form Narratives

• URL: http://arxiv.org/abs/2406.10190v2
• Date: Wed, 26 Jun 2024 14:22:18 GMT
• Title: CHIRON: Rich Character Representations in Long-Form Narratives
• Authors: Alexander Gurung, Mirella Lapata,
• Abstract summary: We propose CHIRON, a new character sheet' based representation that organizes and filters textual information about characters. We validate CHIRON via the downstream task of masked-character prediction, where our experiments show CHIRON is better and more flexible than comparable summary-based baselines. metrics derived from CHIRON can be used to automatically infer character-centricity in stories, and that these metrics align with human judgments.
• Score: 98.273323001781
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Characters are integral to long-form narratives, but are poorly understood by existing story analysis and generation systems. While prior work has simplified characters via graph-based methods and brief character descriptions, we aim to better tackle the problem of representing complex characters by taking inspiration from advice given to professional writers. We propose CHIRON, a new `character sheet' based representation that organizes and filters textual information about characters. We construct CHIRON sheets in two steps: a Generation Module that prompts an LLM for character information via question-answering and a Validation Module that uses automated reasoning and a domain-specific entailment model to eliminate false facts about a character. We validate CHIRON via the downstream task of masked-character prediction, where our experiments show CHIRON is better and more flexible than comparable summary-based baselines. We also show that metrics derived from CHIRON can be used to automatically infer character-centricity in stories, and that these metrics align with human judgments.

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