What the data for this category looks like
Data sources for industrial park intelligent due diligence reports include planning approval documents publicly released by park management committees, internal ledgers from park operators, third-party due diligence drafts, and land transfer-related documents. Update frequency varies significantly by document type: planning documents update dynamically alongside project adjustments, operational documents update monthly or quarterly, and settled enterprise ledgers adjust in real time as enterprises enter or exit the park. Document structures include long-text industrial positioning paragraphs, structured list tables, annotated park floor plans, and attached scanned copies. Core fields include total planned construction area (square meters), actual available construction area (square meters), individual rental area (square meters), monthly rent standard (yuan per square meter), annual operating costs (ten thousand yuan), and industry classification of settled enterprises, among others. Some documents contain watermarks or low-resolution scanned content.
What constraints these characteristics impose on document parsing and chunking
The mixed layout of industrial park due diligence documents can cause conventional chunking tools to split tables into scattered paragraphs, so chunking logic that preserves table structure is required. Long-text planning paragraphs and structured tables distributed across multiple pages require chunking tools to identify cross-page related content to avoid splitting critical context. Low-resolution scanned copies and watermarks can interfere with OCR recognition accuracy, so parsing processes adapted to blurry fonts and watermark interference are needed. There are significant differences across document formats, ranging from official standard PDFs to non-standard Excel ledgers and handwritten scanned copies, so multi-format parsing logic must be supported. Some documents contain a large number of repeated industry classification fields, so redundant splitting of duplicate content should be avoided during chunking.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 300-600 seconds | Industrial park due diligence documents are mostly long documents containing multi-page tables and scanned copies, requiring longer parsing time to complete full content extraction |
maxChunkSize | 800-1200 characters | This range preserves contextual connections between long planning paragraphs and cross-page tables, avoiding forced splitting of structured content |
PARSE_ENABLE_TABLE_EXTRACT | Enabled | Due diligence reports contain a large number of structured tables such as settled enterprise lists and cost details, retaining table structure improves subsequent chunking accuracy |
UPLOAD_FILE_MAX_SIZE | 500-1000 MB | Park planning documents may include high-definition images and multi-page attachments, requiring support for large file uploads |
PARSE_OCR_QUALITY_THRESHOLD | 0.6-0.8 | Balances recognition accuracy for low-resolution scanned copies and watermarked documents, avoiding recognition failures from overly high thresholds and insufficient precision from overly low thresholds |
customParseScript | Calibrated based on actual testing | Some non-standard due diligence drafts require custom scripts to handle specific field formats, and script logic must be adjusted based on actual document types |
The parameter values provided on this page are common recommendations used as a starting point for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require case-by-case analysis, and it is recommended to test on your own samples before finalizing settings.
Three Common Errors
- Symptom: A connection failure error is returned when calling marker-pdf to parse documents. When deploying the docker version v4.8.14 locally, an error still occurs when trying to call via 127.0.0.1. Cause: The intranet access address of marker-pdf was not correctly configured in the docker container. The container's internal network is isolated from the host network, so directly using 127.0.0.1 cannot access the parsing service across containers.
- Symptom: After uploading an industrial park due diligence document, table fields in the parsing result are empty or split into scattered text, or cross-page table related content is missing from the chunking result. Cause: The
PARSE_ENABLE_TABLE_EXTRACTconfiguration is not enabled, or the segment length is set too small, causing tables to be forcibly split. - Symptom: The custom parsing script does not take effect in the parsing result, and adding field processing logic has no response. Cause: The script trigger timing was not correctly bound in the FastGPT custom parsing interface, or the script syntax has format errors that were not recognized.
How to Confirm Proper Configuration
- Upload a typical industrial park due diligence PDF document, check if tables in the parsing result fully retain their structure with no scattered split content.
- Check the parsing task duration in system logs to confirm no timeout errors exceeding the
PARSE_FILE_TIMEOUT_SECONDSconfiguration occur. - Test uploading documents in different formats, such as scanned PDFs and Excel ledgers, to confirm that chunking content can be normally generated for parsing results.
- Trigger a parsing task after editing the custom parsing script, check if the field processing logic defined in the script is applied in the result.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.