What this category of data looks like
Data is sourced from work safety supervision systems, enterprise hazard self-inspection systems, law enforcement inspection records, and accident statistics systems, with a daily update frequency. Daily documents include hazard inspection lists, hazard management ledgers, rectification notices, review records, and major hazard suspension and supervision orders. Most use a mixed format of structured tables and semi-structured text, with fields including hazard ID, inspection time, rectification responsible person, rectification deadline, review result, and others. There is no unified fixed naming convention, and some documents contain handwritten scanned copies or cross-page tables.
Constraints Imposed by These Characteristics on Document Parsing and Chunking
Multi-source and heterogeneous document formats require parsing adapted to mixed structures. Cross-page tables and semi-structured text must retain field association relationships. The daily update frequency requires efficient parsing processes to avoid excessive time spent on single-file processing. Fields are scattered across different documents, so chunking must retain contextual associations to ensure complete field integrity for full-process tracking of hazard rectification. A certain proportion of scanned documents exist, so adaptation to OCR parsing requirements is needed. Field naming varies across different documents, so chunking must not damage field semantic associations.
Configuration Settings
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Matches the length of single hazard field groups in documents such as hazard inspection lists and rectification notices, retaining complete contextual information for hazard-related details |
chunkSplitter | Split by paragraph + table | Adapts to hazard document structures mixing text and tables, avoiding splitting that breaks field associations such as rectification responsible person and rectification deadline within tables |
customPdfParse | Enable table recognition + OCR fallback | Covers parsing requirements for scanned rectification notices and cross-page major hazard suspension and supervision orders, retaining complete table field integrity |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Adapts to the daily update data processing rhythm of multiple files per batch, avoiding task failure due to oversized files or excessive OCR processing time |
chunkSettingMode | Manual configuration | Adjust chunking parameters for different document types (lists/ledgers/notices) to meet field association requirements for full-process tracking of hazard rectification |
Three Common Configuration Mistakes
- Symptom: Chinese text appears garbled after OCR parsing, and core fields are empty. Cause: No OCR fallback parameter adapted to Chinese is configured, or the multilingual recognition mode is not enabled.
- Symptom: After parsing a single PDF file, hazard entries matching the query cannot be accurately matched, and returned results are scattered. Cause: The
chunkSizeconfiguration is too large or too small, failing to retain complete context for a single hazard entry, or thechunkSplitteris not set to split by paragraph, leading to semantic fragmentation. - Symptom: Table content is missing from chunks after parsing a single PDF file, and tables are displayed in the knowledge base but not in output results. Cause: The table recognition switch in
customPdfParseis not enabled, orchunkSplitteris configured to split only by character count, failing to retain table structure.
How to Verify Proper Configuration
- Upload a typical scanned rectification notice for hazards, check that the parsing result retains core fields such as rectification responsible person and rectification deadline, with no garbled text or missing content.
- Import a batch of daily update documents of the same type, check that parsing task durations meet expectations, with no batch timeout errors.
- Initiate a query such as "query the rectification status of a batch of hazards" against the parsed knowledge base, confirm that returned results include complete field association information, with no semantic loss caused by chunk fragmentation.
- Check the configuration status of
customPdfParse, confirm that table recognition and OCR fallback are both enabled to adapt to mixed-format documents.
The values listed here are common starting points and should be assessed against the samples being used.
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.