Semantic Action Graph: A Shared Representation for Agent Grounding and Human Interpretation of Sports Highlights
Read the original on arXiv AI →The paper introduces the Semantic Action Graph, a lightweight domain schema that models a sports match using performer, action, recipient, moment, and state nodes linked by role, temporal, and outcome edges. This structure supports both an agentic pipeline for generating narrated highlights and a visual interface that lets viewers query and inspect the same representation. In a prototype called SportSAGE, 12 soccer fans reported satisfaction with the generated highlights and used the graph interface to search, navigate, and interpret match moments.
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