Building a Narrative Event Dataset from Andersen’s Fairy Tales for Literary and Computational Analysis

Erna Daniati, Aji Prasetya Wibawa, Wahyu Sakti Gunawan Irianto

Abstract


This paper describes building a narrative event dataset for the entire set of 153 fairy tales written by Hans Christian Andersen as?a resource for literary analysis and computational research. The corpus is?built up through semi-automatic annotation for important narrative events: character actions, period transitions, causal communications, and story themes. Each event is augmented with? metadata such as event type, event participants, event temporality (order) and event thematic relevance. This computer-readable structured data is helpful for NLP applications like event detection and temporal reasoning. Still, it supports in-depth literary?studies of plot structures, moral themes and character archetypes in Andersen's stories. Linking the digital humanities with the domain of computational linguistics, the dataset can be jointly used in inter-disciplinary research, and has the potential to reveal new aspects of classical narrative forms and how these findings?and developments can be usefully integrated in AI-supported storytelling systems.


Keywords


Computational Narrative, Digital Humanities Dataset, Fairy Tales Corpus, Narrative Event Extraction, Temporal and Causal Relations

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References


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DOI: https://doi.org/10.52088/ijesty.v5i3.910

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