What This Category of Data Looks Like
Daily business documents for pension, work injury, and unemployment benefit verification include benefit application forms, payment period certificates, retirement approval forms, work injury certification materials, unemployment insurance benefit application materials, and similar items. Data sources include social insurance handling systems, personal social insurance contribution records, labor relations and work injury certification systems, and the electronic social security card platform. The update frequency is daily. Most documents are standardized business forms or structured text. They contain core business fields such as payment period, benefit standard, and application eligibility conditions. No additional custom statistical figures or regulatory provisions are included.
What Constraints Do These Characteristics Impose on Document Parsing and Chunking
High-frequency daily updated business data requires parsing processes to support batch document processing. The fixed field structure of standardized documents means chunking must not break core business information. Format differences across document types require parsing tools to support both standardized text exported from systems and manually filled scanned documents. The accuracy of core fields directly impacts benefit calculation results. Parsing and chunking must retain contextual connections between fields to avoid breaking business logic after splitting. Batch-uploaded document packages may contain multiple materials, so the system must support reasonable resource allocation for batch parsing.
How to Set Configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Documents contain continuous business fields such as payment period and benefit standard, to avoid losing contextual connections after splitting |
chunkSplitter | Split by paragraph + title | Social security business documents often have clear business node titles, to retain the binding relationship between titles and corresponding content |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Large work injury certification materials may contain multi-page attachments and images, requiring sufficient time to complete full parsing |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Batch-uploaded benefit application material packages may contain multiple types of business documents |
customPdfParse | Enable structured parsing | Standardized social security documents mostly have table structures, and structured parsing can fully extract core business fields |
chunkSettingMode | Manual configuration | For different types of business documents, chunking parameters can be flexibly adjusted to adapt to specific formats |
Three Common Mistakes
- Phenomenon: Markdown-formatted benefit verification tables are truncated after output, and cannot fully display application information. Cause: The
chunkSizeparameter was not adjusted, causing long tables to be split and lose contextual connections. - Phenomenon: After uploading a docx file containing multiple work injury certification photos, the returned result prompts Invalid image file. Cause: Image association parsing for
customPdfParsewas not enabled, or the embedded image format in social security documents was not adapted. - Phenomenon: The knowledge base parsing log continuously reports slow operation xxxxms, and MongoDB response is normal. Cause:
PARSE_FILE_TIMEOUT_SECONDSis set too short, and large payment period certificate documents time out before parsing is completed.
How to Confirm the Configuration Is Correct
- Upload a single standardized benefit application form, check if the parsed text fully retains core fields such as payment period and application amount.
- Upload work injury certification materials containing multiple embedded images, confirm that the text descriptions associated with the images in the parsing results are not lost.
- Batch upload 10 documents of the same type, check if the parsing time meets the preset
PARSE_FILE_TIMEOUT_SECONDSthreshold. - View the parsing logs of FastGPT v4.17.0, confirm that there are no slow operation related errors.
The values provided are common starting points and should be measured against the reader's 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 2026-09-28.