Unverified50% confidenceConceptExact time
Paragraph-level retrieval splits documents into chunks of around a few hundred characters, each chunk being vectorized separately and indexed, in order to improve recall precision and directly locate specific content.
1
Sources
50%
Confidence
Long-term
Relevance
10/14/2026
First Seen
Sources
Related Entities
Related Claims
Unverified父子块策略将文档同时索引为大块和小块,检索时用小块精准定位,生成时返回大块提供完整上下文78% similarUnverifiedThe tree index works by splitting long documents into leaf nodes, summarizing adjacent leaf node content to generate parent nodes that aggregate layer by layer to form a summary tree, and during retrieval traversing top-down from the root node to locate text segments.73% similarUnverifiedThe biggest bottleneck when scaling context is historical tool outputs, including text chunks from past retrievals, tool call and result pairs, and file search records.70% similarVerifiedRAG addresses the limitation of large models' knowledge cutoff dates by splitting private documents into text chunks, converting them into vector representations stored in a vector database, and injecting retrieved relevant content into the Prompt.69% similarUnverifiedAn inverted index maps terms to the list of documents containing those terms and is the core data structure of full-text search engines.69% similar
Cite This Claim
Stable URI
https://kongchang.com/claim/1025148API
curl https://kongchang.com/api/v1/knowledge/claims/1025148MCP
get_claim(id=1025148)