EAGER: Corpus-Based Narrative Semantics

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This Early-concept Grant for Exploratory Research (EAGER) explores approaches for computational analysis of narrative. Despite the ubiquitous nature of narrative, computational linguists have shied away from research on narrative since the 1970's, viewing analysis of stories and literature as too difficult. The goal of this EAGER project is to show that analysis of narrative is now possible and that its study can also be relevant to the development of practical, web-based systems. The project features the development of a declarative, symbolic representation of narrative, a method for manually analyzing the content units of narrative using this representation, and a computational approach for automatically processing a corpus of narratives to derive structural and content-oriented patterns. For example, a learning model may be developed to identify and describe dilemmas that a character faces or to identify thematic similarity between stories. In the first 12 months of the project, researchers are focusing on the development of the annotation methodology, a collection project for annotations of short fables and parables, and the development of learning algorithms. In the following six months, the researchers plan to apply the work to a larger domain in order to show larger impact -- namely, the processing of news text for tasks such as summarization. The project features a collaboration between computer scientists and an expert in literary theory in order to incorporate modes of analysis that are well-grounded from the perspective of narratology. The researchers will provide a range of resources for further work in the narratology and computational linguistics communities, including the annotated corpus and annotation methodology (called DramaBank) as well as software for annotation and automatic analysis; these will enable both communities to continue a new line of research on literature and other forms of narrative occurring on the web.