What the data for this category looks like
Power grid equipment-related research report data sources include public reports from power industry associations, national and local grid public tender documents, brokerage power grid equipment sector research reports, and regular announcements from listed companies. Data update rhythm follows event and report cycles: tender documents are updated monthly, and annual reports are released per fiscal year. Documents include structured tables such as equipment parameters, winning bid details, and capacity breakdowns, long-text industry analysis, and multi-column data lists. Fields cover rated power, voltage level, delivery lead time, and more. Units mostly use professional power industry units such as megawatts (MW), kilovolts (kV), units/sets.
What constraints do these characteristics impose on document parsing and chunking?
The multi-source mixed structure of power grid equipment research reports imposes multiple constraints on the parsing and chunking process. First, a large number of structured tables with professional parameters and multi-column detailed data. Chunking by general character length will split parameters from their associated units and destroy the integrity of individual equipment data. Second, documents mix long-text analysis and structured lists. Distinguish between paragraph and table boundaries to avoid forcibly merging preceding and following analysis text with table content. Third, the strong binding between professional terms and units requires the parsing process to retain the association between numerical values and units, preventing the inability to restore complete parameters after chunking. Fourth, batch upload requirements for multiple batches of tender documents require avoiding merging historical documents with currently uploaded files during parsing.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_TABLE_MODE | preserve_structure | Power grid equipment research reports contain a large number of tables with professional parameters. Preserving structure avoids errors in splitting parameters and units |
CHUNK_SIZE | 800–1200 characters | Power grid equipment research reports include both long-text analysis and multi-column equipment detailed data. This range balances context integrity and retrieval accuracy |
CHUNK_OVERLAP | 15–20% | Professional terms and parameters often appear across sections. Overlap ensures complete retrieval of associated information |
UPLOAD_FILE_MAX_SIZE | 500 MB | Large power grid tender summary documents usually do not exceed this threshold, avoiding parsing timeouts |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Structured parsing of multi-page large research reports requires sufficient time to prevent mid-process interruptions |
AUTO_CHUNK_STRATEGY | by_section_and_table | Power grid documents mix long text and tables. Chunking by section and table boundaries preserves content integrity |
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 specific analysis, and it is recommended to test on your own samples before finalizing settings.
Three Common Mistakes
- Phenomenon: After uploading a multi-column equipment detail Excel file, automatic chunking splits each row of data into scattered fragments, failing to retain the complete parameters of a single piece of equipment. Cause: Row-level structured chunking is not configured, and default segmentation by character length destroys the association between multi-column data.
- Phenomenon: When batch uploading power grid tender documents, the parsing log shows previously uploaded documents are also loaded, causing old data to be mixed into the chunking results. Cause: The historical document merge switch for batch parsing is not turned off, and the system merges all uploaded files for parsing by default.
- Phenomenon: After uploading a PDF research report with scanned tables, the equipment parameter fields in the parsing result are empty. Cause: OCR parsing mode is not enabled, and the system cannot recognize structured data in scanned tables.
How to Confirm Proper Configuration
- Upload a single power grid equipment tender Excel file, check whether the chunking result retains the complete information of each equipment's model, unit price and delivery lead time, and adjust the corresponding configuration items until the expected result is achieved.
- Upload a multi-page research report PDF that mixes text and tables, confirm that the parsing result does not incorrectly merge tables with preceding and following text, and verify whether the table parsing mode configuration takes effect.
- Batch upload documents from a single batch, check that the parsing task only processes the currently uploaded files with no historical documents mixed in, and confirm that the batch parsing switch is set correctly.
- Upload a document with scanned tables, confirm that the OCR parsing module is enabled, and check whether the parameter fields are correctly recognized.
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.