Why is our vector search accuracy dropping when we query documents longer than four thousand tokens and how do we fix it?
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Fan-out diagram
The searches the AI actually ran for this prompt.
SEED QUERY
Why is our vector search accuracy dropping when we query documents longer than four thousand tokens and how do we fix it?
1 real search · 1 real-search pass
embedding model input token limits truncation long documents semantic chunking vector search retrieval accuracy recommendationsGoogle ↗
OBSERVED
Badge and edge weight = share of passes that produced the query. Hover a query for its intent and routing format.
Query classes
Google's semantic query class for every sub-query: what kind of answer each search is after, simulated vs real.
Classifying 1 queries…
Searches and sources
ChatGPT1 real searches · gpt-6
embedding model input token limits truncation long documents semantic chunking vector search retrieval accuracy recommendations Google ↗
- Chunk Documents - Azure AI Search · learn.microsoft.com
- Azure AI Search: Outperforming vector search with hybrid retrieval and reranking · techcommunity.microsoft.com
- How content chunking works for knowledge bases · docs.aws.amazon.com
- Chunking Parameters · docs.digitalocean.com