2.3 KiB
Retrieval Layer
This context defines how PaperForge finds papers and fetches evidence from them. It covers lookup intents, retrieval units, and navigation concepts specific to paper-native retrieval.
Language
Retrieval Unit
The smallest typed paper-native object that can be indexed, recalled, and shown to a user or agent. Avoid: chunk, text blob, paragraph group
Body Unit
A retrieval unit built from section-aware body content and used for corpus-level evidence recall. Avoid: paragraph trio, generic chunk
Object Unit
A retrieval unit built from a figure or table plus its grounded local evidence. Avoid: asset, image chunk, caption blob
Structure Tree
The navigable section and object outline of one paper. It is the primary surface for in-paper navigation after a paper has been located. Avoid: TOC dump, outline text
Paper Manifest
The per-paper build control record for retrieval outputs, including hashes, versions, and unit counts. Avoid: vector index, chunk cache
Intents
Paper Lookup
The task of locating a specific paper identity from title, author, year, DOI, citation key, or incomplete bibliographic evidence. Avoid: search, retrieve
Content Discovery
The task of finding which papers discuss a concept, method, comparison, or phenomenon across the corpus. Avoid: paper lookup, title search
Paper Navigation
The task of understanding a located paper's structure before fetching a specific section or evidence block. Avoid: semantic retrieval, full-library search
Scoped Fetch
The task of pulling exact content from a known paper, section path, node id, or narrow local scope. Avoid: global search, blind retrieval
Retrieval Semantics
Structure-first
The rule that retrieval boundaries should be derived from paper structure and object boundaries before text chunk sizing concerns. Avoid: regex-first, paragraph-first
Trust-neutral
The rule that OCR health does not apply a paper-level retrieval penalty. OCR diagnostics may veto local junk units but must not hide an otherwise important paper. Avoid: low-quality paper, degraded paper penalty
Local Junk Veto
The rule that only clearly bad local units such as reference pollution, empty fragments, garbled text, or repeated header/footer noise are excluded from retrieval. Avoid: quality filter, paper-level exclusion