What data for this category looks like
Data sources for military electronic intelligent due diligence include public annual reports of military industrial groups, qualification documents of supporting manufacturers, industry chain research reports, bidding announcements, and military standard documents. Update frequency varies by document type: annual reports are updated per fiscal year, bidding announcements are updated monthly or quarterly, and qualification documents are updated alongside changes to manufacturing scope. Most documents are in PDF format, with some being scanned copies. Document structures include structured parameter tables, qualification description paragraphs, and industry chain production capacity data. Fields cover component models, power, operating temperature, and delivery lead times. Units commonly used include watts, degrees Celsius, calendar days, and other standard industry units.
What constraints do these characteristics impose on document parsing and chunking
The characteristics of military electronic due diligence documents impose multiple constraints on parsing and chunking. Scanned qualification documents require OCR preprocessing, which increases parsing time. Structured parameter tables have mixed units across columns, so chunking must retain field associations to avoid splitting that breaks parameter integrity. Bidding announcement section information is scattered, so chunking must follow section boundaries instead of solely using paragraph length. Some documents contain sensitive classified fields, which must be identified and marked during parsing. Cross-chapter parameters in long documents require retaining contextual associations to prevent critical information from being split apart.
How to configure settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
OCR_ENABLED | Set to enabled for scanned documents, disabled for non-scanned documents | Required to extract text from scanned qualification documents in military electronic materials; no extra OCR steps needed for non-scanned PDFs |
PARSE_SEGMENT_LENGTH | 800–1200 characters | Balances chunking needs for short parameter fields and long analysis paragraphs in military electronics, avoiding splits that break associated information |
TABLE_PRESERVE_STRUCTURE | Enabled | Retains column structure of parameter tables, preventing misaligned splitting of associated fields such as model, power, and delivery lead time |
PARSE_CHUNK_OVERLAP | 100–150 characters | Covers contextual associations across sections and chapters, preventing critical parameters from being truncated by chunking |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Accommodates OCR and parsing time for long documents, preventing parsing failures due to timeout |
UPLOAD_FILE_MAX_SIZE | 500 MB | Meets single-file size requirements for multi-section bidding documents and annual research reports in military electronics |
The parameter values provided on this page are common recommended starting points 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 against your own samples before finalizing settings.
Three common mistakes
- Symptom: After uploading a PDF document with embedded images or scanned copies, the parsing result has no corresponding text content, and key parameter fields are empty. Cause: The
OCR_ENABLEDconfiguration item is not enabled, or the OCR model is not adapted to technical drawings and parameter charts in military electronic documents. - Symptom: Parsed chunked content has cross-chapter splicing, or core parameters are split into multiple independent chunks. Cause:
PARSE_SEGMENT_LENGTHandPARSE_CHUNK_OVERLAPare not configured correctly, or their values do not match the chapter hierarchy of the document. - Symptom: In the knowledge base creation workflow, table-format military electronic documents cannot be selected as parsing datasets. Cause: The table structure retention configuration item is not enabled, or the uploaded table file format is not recognized by the system.
How to confirm the configuration is correct
- Upload a single scanned qualification document, check if the parsing result includes complete qualification text and parameter fields, to confirm the
OCR_ENABLEDconfiguration is active. - Upload a table document with multiple columns of parameters, verify that the chunked result retains column associations for the table, to confirm the
TABLE_PRESERVE_STRUCTUREconfiguration is active. - Upload a single long document, check if the parsed chunks are split according to chapter hierarchy, to confirm the paragraph depth configuration matches the document structure.
- View the parsing task logs, confirm no timeout errors occur, to confirm the
PARSE_FILE_TIMEOUT_SECONDSconfiguration value is reasonable.
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.