Ask Kalicube

Hierarchical Indexing Annotation Proof Dimensions is the technical implementation of Hierarchical Proof Dimensions during the Index phase of DSCRI. When bots process content chunks, they identify and tag hierarchical proof signals: (1) Recognition signals - markers of notability (awards, titles, "industry leader," "recognized expert"); (2) Parentage patterns - language indicating source authority ("according to," "as defined by," "citing," attribution phrases); (3) Connectivity markers - co-mentions with known peer authorities (appearing alongside established experts in the same context). Each annotation receives a confidence score. Connectivity tagging relies on entity recognition - the bot must identify both entities to tag the connection.

Bots map authority networks. When content says "according to Jason Barnard," the bot tags: Parentage="source citation" [0.94]. When your name appears alongside Michael King and Lily Ray, the bot tags: Connectivity="peer cohort" [0.89]. The bot is building a graph of who cites whom, who appears with whom. Your position in that graph determines your algorithmic authority.

Hierarchical Indexing Annotation Proof Dimensions explains how bots technically identify authority signals. During indexing, bots extract recognition markers, identify citation/attribution patterns, and map entity co-occurrence. This creates implicit authority graphs even without explicit schema markup. High-confidence hierarchical tagging requires clear attribution language and recognized entity mentions.