What the data for this category looks like
Coal chemical industry financing daily report data is sourced from public project financing disclosures from domestic coal industry monitoring institutions, and record filing public notices from local energy authorities. Updates occur every working day. Same-day data is integrated and released in the early morning of the next day. Documents use a single project entry structure, with fields including project subject name, financing scale, funding source type, product category, production area, and record filing number. Financing scale uses RMB 100 million yuan as its unit. Exclusive coal chemical production capacity indicators use 10,000 tons per year as their unit. Product subcategories include coal-to-olefins, coal-to-natural gas, coal-to-ethylene glycol, and other similar types.
Constraints on model access and configuration
The exclusive fields and update rhythm of coal chemical industry financing daily reports create three constraints for model access and configuration. First, exclusive fields such as product category, record filing number, and production capacity index require the model to accurately identify industry terminology and match fixed mapping rules. Custom extraction templates must be configured. Second, the number of daily batch-updated entries fluctuates. Batch processing timeout and sharding settings must be adapted to avoid task interruptions. Third, data sources have format differences. Field alignment rules must be configured to ensure unified import of disclosure content from different channels.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
custom_field_mapping | Configure the mapping rule as "project subject → financing scale → product category → production area → record filing number" | Matches the fixed field structure of coal chemical industry financing daily reports to avoid field misalignment |
batch_process_timeout | 1200 seconds | Adapts to the processing duration of multi-entry data pulled in batches daily to avoid mid-process timeout interruptions |
embedding_model | Connect to embedding-v1 or bge-large-zh-v1.5 | Adapts to semantic recognition of coal chemical industry professional terminology to improve recall accuracy |
max_context_length | 8000 characters | Adapts to the text length of a single financing daily report project to avoid truncation of key information |
duplicate_check_field | Configure as "record filing number" | Uses the unique identifier field to remove duplicate imported project entries |
schedule_interval | Trigger daily at 9:00 | Matches the update rhythm of financing daily reports to ensure data timeliness |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require case-by-case analysis, and it is recommended to test on your own samples before finalizing settings.
Three Common Misconfigurations
- When connecting
embedding-v1via OneAPI, a 404 error is returned. The cause is that the model's interface path and authentication key are not correctly filled in the gateway configuration. - When batch importing financing daily report projects, the product category field may be empty. The cause is that the
custom_field_mappingrule is not configured, so the model cannot match the exclusive product classification field for the coal chemical industry. - Scheduled pull tasks time out. The cause is that the
batch_process_timeoutsetting is lower than the actual processing time of batch data, and the number of newly added projects on the day is not accommodated.
How to Confirm Configuration is Complete
- Manually import single test data from coal chemical industry financing daily reports. Check whether field extraction results include exclusive fields such as product category and record filing number to confirm that the configuration takes effect.
- Initiate a small-scale batch test. Check whether the task is completed within the duration set by
batch_process_timeoutto confirm that the timeout configuration is reasonable. - Import test data containing duplicate record filing numbers. Check whether the system automatically completes deduplication to confirm that the deduplication rule configuration is correct.
- Trigger a scheduled scheduling task. Check whether the pulled data matches the daily updated financing daily report entries to confirm that the scheduling interval matches the update rhythm.
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.