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What is Training corpus?

The dataset an LLM was trained on. Brands that appear frequently and consistently in the training corpus are recalled by name in answers, with no live retrieval required.

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Definition

Training-corpus presence is the single most important signal for non-grounded LLM surfaces (default ChatGPT, Claude, ungrounded Gemini). You buy presence by being everywhere LLM training pipelines scrape: Wikipedia, Reddit, GitHub, established publishers, G2/Capterra, broad press coverage.

Why it matters

Training corpus sits in the "Signals & ranking" layer of the AI search stack. Teams that handle it well get cited more, recommended more, and earn more of the AI-mediated revenue in their category. Teams that ignore it spend a year wondering why their content investment never moves the needle inside ChatGPT or Perplexity.

Related terms

  • LLM SEO - Optimizing for Large Language Models - making sure ChatGPT, Claude, Gemini, Perplexity, and Grok know about, cite, and recommend your brand.
  • Cross-source consensus - How consistently many independent sources describe a brand the same way. The single biggest factor in whether an LLM names a brand by default.
  • Mention rate - The percentage of prompts in a defined panel where an LLM names your brand. The headline metric of LLM SEO programs.

Apply it

The LLM SEO playbook ties every concept in this glossary into a single operating model. If you want to see how your brand performs across all the LLMs at once - mention rate, citation share, sentiment, rank - start with the free GEO audit or skip straight to a free Livesov account.

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