Canonical Tags and Training Data Deduplication
Duplicate content has been a nuisance for classic SEO for decades, leading to “cannibalization” and split PageRank. In the era of Large Language Model (LLM) training, duplicate content is a much more structural problem. It leads to biased weights and model overfitting. To combat this, pre-training pipelines use aggressive deduplication algorithms like MinHash and SimHash.
The Deduplication Pipeline
When organizations like OpenAI or Anthropic build a training corpus (e.g., from Common Crawl), they run deduplication at a massive scale. They might remove near-duplicates to ensure the model doesn’t over-train on viral content that appears on thousands of sites.