What this category of data looks like
Ordnance and equipment investment research data comes primarily from publicly available national defense and military industry research reports, official announcements from military industry groups, industry technical standard documents, equipment bidding and tendering public notices, and official technical manuals. Update frequency aligns with industry dynamics: quarterly industry research reports are updated on a regular basis. Temporary documents are released when major equipment technology iterations or procurement policy changes occur. Most documents are PDF files with multi-page charts. They include structured fields such as equipment model parameters, performance metrics, and test data. Units use specialized military measurement units including millimeters, kilometers, kilograms, rounds per minute, and others. Some documents embed non-text elements such as equipment disassembly schematics and performance curves.
What constraints do these characteristics impose on document parsing and chunking?
Ordnance and equipment investment research documents often embed non-text elements like equipment schematics and performance curves. Systems must support image text extraction to fully retrieve parameter information. Documents contain large volumes of structured parameters paired with specialized units. Chunking processes must avoid splitting numerical values from their associated units to prevent loss of parameter data. Some bidding and tendering documents are very long. Parsing logic must handle long text inputs. Quarterly research reports and temporary technical announcements also require the parsing workflow to run efficiently. Document chapter hierarchies vary widely across sources. Parsing processes must preserve original structural relationships to avoid mixing parameters from different chapters.
How to configure the system
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
PARSE_IMAGE_ENABLE | Enabled | Ordnance and equipment documents embed large numbers of non-text elements such as equipment schematics and performance curves. Extracting text from images is required to fully retrieve all parameter information |
PARSE_CHUNK_SIZE | 800–1200 characters | Documents contain large volumes of structured parameters with specialized units. This range avoids splitting numerical values from their associated units while retaining contextual connections |
PARSE_CHUNK_OVERLAP | 10–15% | Preserves linked information before and after parameter paragraphs. This prevents breaks in performance metrics and model information across chunks |
UPLOAD_FILE_MAX_SIZE | 500 MB | Supports uploads of lengthy files such as large bidding documents and annual industry white papers |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Reserves enough processing time for image parsing and text extraction from large PDF files |
TEXT_SPLITTER_MODE | Paragraph and semantic splitting | Preserves paragraph integrity for equipment parameters. This avoids splitting blocks of identical technical metrics |
The parameter values provided on this page are common starting points for configuration setup. Actual values will vary based on material format, data volume, and business rules. Specific scenarios require targeted analysis. Test configurations on sample datasets before finalizing settings.
Three common configuration mistakes
- Phenomenon: Knowledge base recall results do not include text from embedded PDF equipment schematics, or extracted image text is incomplete. Cause: The
PARSE_IMAGE_ENABLEconfiguration item is not enabled. The system only extracts plain text and misses parameter data stored in images. - Phenomenon: Chunking results split numerical values from their associated specialized units, or a single segment of performance metrics is split across two chunks. Cause: The statistical unit for chunk length is not clearly defined, token count is mistakenly used as the segmentation basis, or segmentation length is set too short, leading to parameter splitting.
- Phenomenon: Large bidding documents fail to parse, returning a
413 Request Entity Too Largestatus code or a parsing timeout alert. Cause: TheUPLOAD_FILE_MAX_SIZEandPARSE_FILE_TIMEOUT_SECONDSconfigurations are not adjusted, exceeding default system limits.
How to verify correct configuration
- Upload a PDF of an ordnance and equipment technical manual that includes embedded images. Confirm parsed results include text parameters extracted from the images.
- Review chunked text fragments to confirm single segments of parameters with specialized units are not split across multiple chunks.
- Upload a large document that exceeds the default upload limit. Confirm upload and parsing processes complete without errors.
- Check system logs or parsing task details to confirm the actual applied status of the relevant configuration items.
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.