Interactions between Narrative Schemas and Document Categories
Year: 2015
Type: conference-paper
Abstract: The unsupervised extraction of narrative schemas—sets of events with associated argument chains—has been explored and evaluated from many angles (Chambers and Jurafsky, 2009; Jans et al. 2012; Balasubramanian et al., 2013; Pichotta and Mooney 2014). While the extraction process and evaluation of the products has been well-researched and debated, little insight has been garnered on properties of narrative schemas themselves. We examine how well extracted narrative schemas align with existing document categories using a novel procedure for retrieving candidate category alignments. This was tested against alternative baseline alignment procedures that disregard some of the complex information the schemas contain. We find that a classifier built with all available information in a schema is more precise than a classifier built with simpler subcomponents. Coreference information plays an crucial role in schematic knowledge.
DOI: 10.18653/v1/w15-4501
Authors: Dan Simonson, Anthony Davis
Institution: Georgetown University
Language: English
Topic: Topic Modeling
Subfield: Artificial Intelligence
Field: Computer Science
Domain: Physical Sciences
Open Access status: gold
OpenAlex ID: W2250734603