Document Parsing and Chunking for Commercial Vehicle Investment Research Knowledge Base Construction

Commercial vehicle investment research data comes from multiple sources: Ministry of Industry and Information Technology motor vehicle product

What Data for This Category Looks Like

Commercial vehicle investment research data comes from multiple sources: Ministry of Industry and Information Technology motor vehicle product announcements, automakers’ annual technical manuals, dealer monthly sales reports, vehicle registration volume statistics, and industry association public reports. Update cycles cover monthly, quarterly, and annual intervals. Document formats include PDF parameter announcements, HTML interface documents, structured table-based vehicle configuration sheets, and promotional materials with charts. Fields include professional parameters such as curb weight, wheelbase, torque, and emission standards. Most units are kilograms, millimeters, and newton-meters. Some price-related fields use ten thousand yuan as the unit.

Constraints for the Document Parsing and Chunking Stage

The multi-source data and varied update cycles mean the parsing stage must support parallel incremental and full processing. This avoids repeated parsing of frequently updated registration volume data. Structured parameter tables in documents bind to long-text technical explanations. During chunking, retain the contextual association between parameters and explanations. Do not split cross-paragraph parameter groups. HTML interface documents contain nested code blocks and parameter tables. Extract fields with precision. For promotional materials with images, parameter information often appears as images. Add OCR processing to extract this data, otherwise core investment research data is lost.

How to Set Configurations

Configuration ItemRecommended ValueRationale
PARSE_FILE_TIMEOUT_SECONDS600 secondsCommercial vehicle technical documents often include long PDFs and multiple parameter charts, with longer parsing times than general documents
chunk_size800–1200 charactersCommercial vehicle documents contain bound professional parameter groups. A value that is too long splits parameters and explanations. A value that is too short breaks contextual associations
ENABLE_OCR_PARSEEnabledCommercial vehicle brochures and announcement PDFs often carry parameter tables as images. OCR extracts structured fields
UPLOAD_FILE_MAX_SIZE1000 MBSome automakers’ annual technical manuals have large single-file sizes. Adapt upload limits to these sizes
PARSE_TABLE_KEEP_STRUCTEnabledCommercial vehicle documents contain many parameter tables. Retaining structure prevents misalignment between fields and units
PARSE_HTML_EXTRACT_TABLEEnabledCommercial vehicle interface documents in javadoc format include parameter tables. Enabling this extracts structured fields

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 targeted analysis, and testing against local samples before finalizing is recommended.

Three Common Mistakes

  • Phenomenon: After uploading a commercial vehicle promotional PDF, the knowledge base only extracts a small amount of plain text and fails to retrieve parameter table content from images. Cause: The ENABLE_OCR_PARSE configuration is not enabled, and the default parsing logic ignores structured data within images.
  • Phenomenon: After uploading a commercial vehicle document in chunk mode, the interface continuously displays the "Indexing" status without progress, or returns a 408 Request Timeout status code. Cause: The set PARSE_FILE_TIMEOUT_SECONDS value is lower than the actual parsing time, or the number of chunks split from a single file exceeds the queue processing limit.
  • Phenomenon: After uploading a commercial vehicle interface HTML document in javadoc format, the knowledge base has no parsed content at all. Cause: The PARSE_TABLE_KEEP_STRUCT configuration is not enabled, and the default HTML parsing does not retain table structure, causing parameter fields to fail identification.

How to Confirm the Configuration Is Correct

  • Upload a single-page commercial vehicle parameter PDF. Check the OCR extraction records in the parsing log to confirm that the ENABLE_OCR_PARSE configuration is active.
  • Upload a javadoc-format interface HTML document. Check whether the knowledge base chunks retain the correspondence between parameter table fields and units to confirm that the PARSE_TABLE_KEEP_STRUCT configuration is enabled.
  • Upload a large commercial vehicle technical manual. Check whether the upload progress completes within the configured timeout period to confirm that the timeout configuration adapts to the current document size.
  • Upload a test file in chunk mode. Check whether the indexing status updates within a reasonable time frame to confirm that the queue configuration adapts to the current business volume.

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.