Story Morals: Surfacing value-driven narrative schemas using large language models (2024)

Abstract: Stories are not only designed to entertain but encode lessons reflecting their authors’ beliefs about the world. In this paper, we propose a new task of narrative schema labelling based on the concept of “story morals” to identify the values and lessons conveyed in stories. Using large language models (LLMs) such as GPT-4, we develop methods to automatically extract and validate story morals across a diverse set of narrative genres, including folktales, novels, movies and TV, personal stories from social media and the news. Our approach involves a multi-step prompting sequence to derive morals and validate them through both automated metrics and human assessments. The findings suggest that LLMs can effectively approximate human story moral interpretations and offer a new avenue for computational narrative understanding. By clustering the extracted morals on a sample dataset of folktales from around the world, we highlight the commonalities and distinctiveness of narrative values, providing preliminary insights into the distribution of values across cultures. This work opens up new possibilities for studying narrative schemas and their role in shaping human beliefs and behaviors.

## introduction as the esteemed literary critic wayne booth once wrote, "all stories teach" @xcite . while we may associate the idea of story morals with short didactic fiction (i.e. fables), narrative theorists have long argued that all stories encode valuedriven schemas in the form of lessons or morals @xcite . as @xcite argue, "narrative schemas enable individuals to organize and represent experiences and/or events as meaningful wholes that function as the bases for comprehension and behavior." stories provide templates for how to live. in this paper, we propose a new task of narrative schema labeling based on the concept of "story morals." a story's moral can be thought of as a short, compressed lesson (often memorable) that a story aims to convey to its audience (see as a narrative schema, story morals differ from other frameworks because they focus on the values and intentions of the storyteller. the focus on a story's moral shifts the locus of attention from the question, "what happened?" to "why was this told?" or "what basic lesson am i supposed to learn from this?" importantly, while story morals are related to questions of moral beliefs, story morals need not explicitly communicate moral sentiments (e.g. "kindness is good"). rather, they can address general lessons that may draw from, reinforce, or challenge larger moral frameworks. it is not uncommon, for example, for individuals to come away from reading a book or watching a movie and reflect on what the writer or director was "trying to say" (as opposed to asking, "what was the moral framework the author was using?") while this interpretive process depends on the specific narrative events, a story's moral is extrapolated from contentlevel features. story morals thus represent an important, yet challenging labeling exercise. as can be seen in the lost camel: a king is initially skeptical of four people who are accused of stealing a camel. impressed by their keen observations and a defence that absolves them of guilt, he recompenses the man who lost the camel, and promotes the four individuals to be his ministers. the us's budget deal is a victory for mike johnson. but for how long? : us house speaker mike johnson juggles new demands about a budget bill from members within his own party and those of the opposing party. what is the moral of the story? good benevolent leadership pays off your own team can turn against you a ruler must be just and righteous conflict can occur within the same group given the importance and cultural prevalence of story morals along with the highly derivative nature of their production, we propose that llms are an ideal candidate for testing the task of automated story moral labeling. while llms continue to struggle with the problem of hallucination @xcite , the derivative nature of story morals, i.e. that a story's message is rarely explicitly stated in the story but must be derived from it, makes for a potentially good fit with llm capabilities. additionally, we assume that given the prevalence not only of stories, but also story-moral-like statements on the web, that this concept is likely well represented in llm training data, with potential cultural biases that need to be assessed. the ability to extract story morals across different kinds of text genres, cultures, and historical time periods can play an important role in supporting the project of computational narrative understanding @xcite . with sufficient quality datasets, the ability to extract story morals can help us better understand the distribution of values across cultures and highlight where there are core differences and where humans share common ground as evidenced by the myriad stories they tell @xcite . in this paper, we make the following contributions: first, we define the task of story moral labeling and create a dataset of human annotated story morals across a diverse set of story types (800 story morals across 6 genres and 144 unique stories including one foreign language (mandarin)). second, we implement both automated and human-level validation schemes for one candidate llm (gpt-4) to illustrate the feasibility of using llms for this task. third and finally, we illustrate the analytical affordances of llm-assisted story-moral labeling on a diverse dataset of folktales from different regions of the world that have been translated into english. ## related work the organization of stories into broad, overarching categories is deeply rooted in the field of narratology @xcite @xcite @xcite . despite addressing narratives at varying levels of abstraction, these models converge on a fundamental premise: stories inherently share common elements, and their selection is orchestrated by higher-level schemas that shape the narrative's construction and interpretation. in the field of nlp, work related to labeling narrative schemas ranges widely across a diverse set of approaches. early work by @xcite focused on narrative schema detection focused on identifying related event chains @xcite @xcite . the chaining together of event schemas has been integral to operationalizing the concept of "plot" @xcite , including plot summaries and plotlines @xcite . other work has focused on detecting higher-level schemas such as "conflict" and "resolution" @xcite , turning points @xcite , folktale motifs (karsdorp and van den bosch, 2013), narrative archetypes such as "rags-to-riches" @xcite , and the more traditional concept of "genre" @xcite @xcite . closer to our work is research focused on identifying narrative intentions, i.e. surfacing the aims guiding why stories are told @xcite . @xcite have explored the detection of narrative intentions in advice-seeking contexts online. their approach seeks to leverage common-sense reasoning to infer the implicit questions and aims embedded in personal stories (see also @xcite . @xcite look at birth stories as a salient genre in which to recover author intentions in online public forums. related to intention, @xcite recently used the concept of story morals in their study of narrative messaging related to climate change. attention to story morals implicitly draws connections to related work on detecting moral sentiment in texts. much of this work derives from the theoretical foundations of @xcite , and has been applied to the study of texts such as tweets @xcite @xcite , folktales @xcite , and across multiple domains @xcite . @xcite provide a useful overview of the use of "morals" as a concept within nlp research. in the next section we highlight how our work aligns and departs from this prior work. ## application we now present a case study to illustrate the analytical affordances of the story morals framework. specifically, we collect morals from the full collection of our fairy tales data source from the validation. it consists of 1,760 tales from 54 cultural groups across all six inhabited continents; a breakdown of the cultural representation is given in appendix b.1. all stories are english translations of the originals. we then apply clustering techniques, based on bertopic @xcite for topic modelling, to group them into clusters and compare our results to those obtained by applying the same method to the full stories directly. we show that our clusters form cohesive units, illustrating lessons and pieces of wisdom related by a common theme, and that these results are qualitatively different from those obtained from the clusters of the full stories. ## conclusion in this paper we endeavored to introduce and validate a new narrative schema framework focusing on the concept of story morals. we showed that this is a well-understood concept by both human annotators and at least one candidate llm (gpt-4), which demonstrates the capacity to produce highvalue annotations in this area. we also showed that when applied to a diverse cultural dataset of folktales, coherent clusters of values and lessons emerged that cut across different cultures. some were more strongly associated with certain regions, indicating a potential cultural preference for moral schemas within storytelling @xcite . our framework also provides the ability to explore messaging in other more contemporary genres. while we have focused our case study on the genre of folktales, our validation suggests that story moral labeling can also be successful on contemporary long form genres like novels, visual narratives such as movies and tv, personal stories from social media, and news media. while we expect each of these domains to pose specific analytical challenges, the story morals framework can be applied to these different domains and potentially surface, for example, core lessons circulated in the news media around key social issues such as climate change or the future of democracy @xcite . the higher level organization of moral clusters seen in our clustering exercise also suggests potential connections to other values-driven frameworks such as moral foundations theory @xcite or schwartz's theory of basic human values @xcite . the value of our method lies in its pluralism, i.e. that it is open to numerous different lessons as opposed to beginning with a specified taxonomy which may or may not be sufficiently representative of cultural behavior. while the clusters we have uncovered are more fine-grained and detailed than the five basic concepts of mft, for example, it is likely that they could fit inside that classification or even express new themes outside that scope. further research will be needed to explore the relationship between our work and other frameworks. finally, the story morals framework can play an important role in the greater workflow of largescale narrative understanding @xcite . story morals represent a foundational narrative schema that shapes how stories are told and what issues are focalized in a given story. in this, they can support the larger narratological project of surfacing both content-level and discourse-level features. story morals provide a valuable way of thinking about narrative schema labeling to understand broader storytelling trends and behavior.