What Data Looks Like for This Category
Coal chemical industry investment research data primarily comes from industry association monthly bulletins, listed companies’ annual and half-year reports, coal chemical project environmental impact assessment reports, professional research reports, and daily commodity price data. Update cycles vary significantly: industry price data updates daily, research reports are released irregularly, and annual reports and EIA reports are updated per project timelines or quarterly.
Document types include long-form research reports spanning dozens of pages, structured statistical tables, official announcements with copyable text, and scanned industry reports. Fields cover production capacity, operating rate, coal consumption per ton of product, coal gasification efficiency, and more. Common units are industry-specific, such as kg standard coal per ton, standard cubic meters per hour, and percentage.
Constraints on Document Parsing and Chunking Workflows
The diverse characteristics of coal chemical investment research data create multiple constraints for the document parsing and chunking process. Long-form research reports account for a large share of the dataset. Chunking must retain chapter logic to avoid forced splitting or merging of cross-chapter process and production capacity content. A high volume of structured statistical tables requires preservation of the original row and column structure, to prevent loss of the association between fields and their corresponding values. Wide variation in data update cycles means incremental parsing needs distinct processing rules for historical documents and newly uploaded files. Abundant industry-specific units and terms require accurate identification and retention during parsing, to avoid truncated professional terms or lost unit information. Some documents use scanned formats. OCR must be used to extract text, otherwise valid content cannot be retrieved.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunk_size | 800–1200 characters | Coal chemical professional documents contain long sentences and exclusive terms. This range preserves the logical integrity of single segments and avoids splitting technical terms. |
chunk_overlap | 100–150 characters | Content such as processes and production capacity in coal chemical research reports has cross-paragraph connections. This overlap length covers the front-and-back continuity needs of key terms. |
PARSE_TABLE_STRUCTURE | Enabled | Coal chemical documents include structured tables for production capacity, unit consumption, prices, and more. Retaining table structure prevents loss of field-value correspondence during searches. |
OCR_LANGUAGE | zh+en | Coal chemical documents contain both Chinese professional terms and English technical annotations. This configuration accurately recognizes both text types. |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Parsing large individual EIA reports or annual industry statistical statements takes significant time. This duration covers most standard parsing scenarios. |
PARSE_PDF_USE_OCR | Force enabled for scanned PDFs, disabled for copyable PDFs | Most coal chemical official announcements use copyable text. Scanned industry reports require OCR recognition to avoid missing post-parsing content. |
The parameter values provided on this page are conventional recommendations used as a starting point for configuration setup. Actual values are affected by material format, data volume, and business rules. Specific issues require individual analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Misconfigurations
- Scenario: After uploading an Excel file containing coal chemical production capacity statistics, the parsed result only shows unformatted plain text, and the table row and column structure is lost. Cause: The
PARSE_TABLE_STRUCTUREconfiguration is not enabled, causing structured tables to be directly converted to plain text. - Scenario: When searching an imported coal chemical research report PDF, only an OCR Error message is displayed or no matching results are found. Cause: OCR recognition is not enabled for the scanned PDF, or the
chunk_sizesetting is too small, splitting professional terms into ineffective retrieval units. - Scenario: The high-precision parsing option is not visible in the upload file interface, and miner-u related functions cannot be enabled. Cause: The FastGPT version is lower than v4.8.0. The miner-u function was integrated into the default parsing process after this version, or third-party parsing plugin permissions are not enabled in system settings.
How to Verify Correct Configuration
- Upload a coal chemical structured Excel table, check if the parsed result retains the correspondence between row and column titles and their corresponding values, to confirm the
PARSE_TABLE_STRUCTUREconfiguration is active. - Upload a scanned coal chemical industry report PDF, check if the parsed result contains complete text content, to confirm the OCR configuration and language parameters match the document content.
- Initiate a knowledge base search test, enter a coal chemical-specific term such as "coal consumption per ton of olefins", check if the returned results include the complete context of the corresponding paragraph, to confirm the
chunk_overlapandchunk_sizeconfigurations are reasonable. - View the parsing task logs, confirm that the parsing duration does not exceed the value set for
PARSE_FILE_TIMEOUT_SECONDS, with no timeout errors.
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.