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The Cookie Theft picture description task is widely used to assess cognitive–linguistic abilities. Analyzing how speakers progress through the 23 content information units (CIUs) in the picture provides insight into the informational relevance and efficiency of their descriptions. Although prior CIU-based studies have shown effectiveness in distinguishing cognitively impaired speakers, they largely rely on manual annotation and focus on spatial CIU distributions, leaving temporal narrative dynamics underexplored. We propose an automated framework for identifying CIUs from picture descriptions and modeling transitions between CIUs as a temporal graph. Graph-based features are extracted to characterize narrative organization and temporal dynamics, and a visualization is designed to illustrate how speakers traverse picture content over time. The framework extends CIU-based analysis beyond spatio-semantic representations and offers a scalable approach for assessing cognitive abilities.