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arXiv · 2104.07079

Modeling Human Mental States with an Entity-based Narrative Graph

I-Ta Lee·Maria Leonor Pacheco·Dan Goldwasser
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Abstract

Understanding narrative text requires capturing characters' motivations, goals, and mental states. This paper proposes an Entity-based Narrative Graph (ENG) to model the internal-states of characters in a story. We explicitly model entities, their interactions and the context in which they appear, and learn rich representations for them. We experiment with different task-adaptive pre-training objectives, in-domain training, and symbolic inference to capture dependencies between different decisions in the output space. We evaluate our model on two narrative understanding tasks: predicting character mental states, and desire fulfillment, and conduct a qualitative analysis.

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BibTeXRIS

I-Ta Lee, Maria Leonor Pacheco, Dan Goldwasser. 2021-04-14. Modeling Human Mental States with an Entity-based Narrative Graph. https://doi.org/10.18653/v1/2021.naacl-main.391

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