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MethodologyPipelineAboutExplore Entidex

Entidex · Signal Layer

How fast do LLMs learn about real-world events?

We probe Claude, ChatGPT, Gemini, Grok and Perplexity at regular intervals and grade their answers against a known ground truth. The result is a live picture of LLM awareness lag — per model, per topic, with retrieval on or off.

Pick an entity to inspect:

AMDARM HoldingsATP FinalsATP TourAWSAWS LambdaAdaptive SortAdidasAdobe After EffectsAdobe After EffectsAdobe Creative CloudAdobe Inc.

LLM awareness over time

Tracking awareness scores for ATP Finals over recent probes.

02550751000probe #2
ClaudeChatGPTGeminiGrokPerplexity

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Entidex Pro tracks awareness lag, sentiment trajectory, intent shifts and citation gaps across every LLM that matters. Explore the platform →

Awareness Matrix

How well each LLM knows ATP Finals — by topic and retrieval mode.

Last probed: 17h ago

General knowledge

ModelRetrieval OFFRetrieval ONUpliftLag (days)
●Claude8579-6—
●ChatGPT8582-3—
●Gemini85850—
●Grok8582-3—
●Perplexity85850—

Recent events

ModelRetrieval OFFRetrieval ONUpliftLag (days)
●Claude6979+10—
●ChatGPT7582+7—
●Gemini72

Current sentiment

ModelRetrieval OFFRetrieval ONUpliftLag (days)
●Claude69690—
●ChatGPT82820—
●Gemini8285
Score≥75≥50≥30>00● mentioned  ·  Uplift = ON − OFF  ·  hover score for probe age
85
+13
—
○Grok6532-33—
●Perplexity8285+3—
+3
—
●Grok6979+10—
●Perplexity8285+3—