Document Parsing and Chunking for Real-World Evidence

Data Characteristics

Real-World Evidence (RWE) quality documents originate from clinical trial institutions, medical device or pharmaceutical manufacturers, and data analysis organizations. These documents have a relatively low update frequency, typically updated during study protocol revisions, data report releases, or regulatory requirements. Document structures are complex, often including study protocols, ethics committee approvals, data management plans, statistical analysis plans, study reports, and informed consent forms. Study reports and statistical analysis plans are often hundreds of pages long, in PDF format, containing numerous tables, figures, and nested headings. Fields involve clinical indicators, biostatistical parameters, drug dosages, and follow-up times, with diverse and strict units like mg/kg, mmol/L, years, months, and days, frequently accompanied by abbreviations and specialized terminology.

Constraints on Document Parsing and Chunking

The complex structure of RWE quality documents poses challenges for document parsing. Deeply nested headings and diverse document types require parsers to accurately identify information boundaries at different levels, preventing semantic fragmentation. Extensive table and figure content necessitates specialized structured extraction capabilities to ensure critical data is not lost and its contextual relevance is maintained. Document update frequency is low, but a single update can involve large-scale revisions, requiring the parsing process to have efficient incremental update identification mechanisms. The strictness of specialized terminology and measurement units makes fine-grained control over text chunking critical. Overly large chunks may dilute key information, while overly small chunks may lose context. Therefore, parsers require refined processing to adapt to the unique information density and structural characteristics of these documents.

Configuration Guidelines

Configuration Item	Recommended Value	Rationale
`UPLOAD_FILE_MAX_SIZE`	`1000 MB`	RWE reports often contain many figures, leading to large file sizes.
`PARSE_FILE_TIMEOUT_SECONDS`	`600 seconds`	Large PDF files take longer to parse; prevents timeout interruptions.
`Chunk size`	`800–1200 characters`	Balances semantic completeness and recall efficiency, avoids information fragmentation.
`Chunk overlap`	`100–200 characters`	Ensures context continuity at chunk boundaries, improves recall relevance.
`Parsing Mode`	`Structured Parsing`	Prioritizes document structure recognition, adapts to complex RWE report hierarchies.
`maxContext`	`4000`	Ensures critical contextual information is complete, prevents truncation of important details.

Common Mistakes

Timeout errors occur when parsing large PDF files because PARSE_FILE_TIMEOUT_SECONDS is set too low, not accounting for the time required to process the file.
Critical table data is lost or incorrectly formatted after document parsing because structured parsing was not enabled or correctly configured, treating table content as plain text.
The knowledge base does not reflect the latest information after document content updates because incremental parsing and index updates are not regularly triggered or effectively managed.

Verification Steps

Select a representative RWE report, upload it, and check the chunked content after document parsing to confirm that key information is complete and contextually coherent.
Choose complex tables and figures from the report and verify that their content is accurately extracted and structured, with no data loss or formatting errors.
Modify a small amount of key information in the report, re-upload it, and check the update status of the corresponding content in the knowledge base to confirm that the incremental parsing and update mechanism is effective.

Note: The values provided are common starting points and should be measured against your own samples.

Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-21.