What the Data for This Category Looks Like
Coal mine production document data comes primarily from on-site operation records, safety management ledgers, dispatch and command documents, and hidden danger investigation reports. Update rhythms vary by document type. Daily inspection records update per shift. Electromechanical equipment ledgers synchronize quarterly. Disaster warning notices generate when events occur. Most documents are semi-structured. They include fixed fields such as equipment number, operation time, and hidden danger level, paired with free text describing on-site conditions. Involved units include meters, megapascals, person-times, and tons.
What Constraints Do These Characteristics Impose on Document Parsing and Chunking
The mixed semi-structured and free text nature of coal mine production documents requires parsing to support both fixed field extraction and long text semantic retention. It must avoid separating professional fields from their associated units and descriptions. High-frequency shift inspection records and sudden disaster warning documents demand fast parsing. They must adapt to timeout limits in high-frequency upload scenarios. For long documents such as quarterly electromechanical ledgers, overly long chunks cause semantic breaks. Overly short chunks disrupt the integrity of professional technical descriptions. A balance must be struck between chunk length and semantic coherence.
How to Configure Settings
| Configuration Item | Recommended Range | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the mixed semi-structured text length of coal mine documents, avoiding splits between professional technical descriptions and associated fields |
chunkSplitter | By paragraph + semantic boundary | Adapts to the mixed fixed field and free text structure of semi-structured documents, retaining associations between fields and descriptions |
customPdfParse | Enabled | Adapts to tabular ledgers and inspection reports common in coal mine documents, preserving field and unit information within tables |
PARSE_FILE_TIMEOUT_SECONDS | 120–180 seconds | Addresses parsing time for long documents such as quarterly electromechanical ledgers, avoiding timeout failures in high-frequency upload scenarios |
chunkSettingMode | Semi-automatic mode | Allows adjustment of chunking parameters for different coal mine document types, such as inspection records and warning notices, to adapt to diverse document structures |
Reference only; verify against the target FastGPT release and deployment documentation.
Three Common Misconfiguration Issues
- Symptom: Parsing task timeout errors occur after uploading long documents such as quarterly electromechanical ledgers. Cause: The
PARSE_FILE_TIMEOUT_SECONDSparameter was not adjusted. The default timeout duration is insufficient to complete full parsing of long documents. - Symptom: Duplicate document chunks appear after custom chunking rules generate chunks stored in the knowledge base. Custom index order fails. Cause: Custom chunking settings were not locked. The system automatically triggered deduplication logic to merge some chunks, leading to index matching failures.
- Symptom: The chunk ID and knowledge base ID fields cannot be selected or copied in the knowledge base list and document chunk details page. Batch association of document chunks and indexes is impossible. Cause: Metadata interaction adaptation was not enabled. The platform did not activate copy buttons for the corresponding fields.
How to Verify Successful Configuration
- Upload a single quarterly electromechanical ledger document. Check the parsed chunk list to confirm chunk length falls within the preset
chunkSizerange. - Upload multiple identical inspection records. Verify no redundant duplicate document chunks appear after parsing. Confirm chunking rules were not automatically modified by the system.
- Check the document parsing log. Confirm the
PARSE_FILE_TIMEOUT_SECONDSparameter did not trigger timeout errors, and parsing time meets expectations. - Enter the document chunk details page. Confirm the chunk ID and knowledge base ID fields support selection and copying, and verify interaction logic works correctly.
The values provided here are common starting points, and should be evaluated against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.