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The semantic action graph is presented, a lightweight domain schema that represents a sports match as performer, action, recipient, moment, and state nodes connected by role, temporal, and outcome edges, providing early evidence that one small, human-readable schema can ground agent generation and support human interpretation at the same time.
It is suggested that audio is an underexplored but highly informative modality for sports highlight detection and should be treated as a primary signal rather than merely an auxiliary cue.
