Knowledge Base Retrieval and Recall for Coal Chemical

What this category’s data looks like

Coal chemical due diligence data sources include project feasibility study reports, industry association industrial operation data, enterprise production logs, and publicly available environmental monitoring documents. Update cycles vary significantly across document types: feasibility study reports are only updated during the project approval phase, industrial operation data is released quarterly, and production logs are updated daily. Most documents use structured tables paired with paragraph explanations, and include modules such as basic project information, process parameters, production capacity indicators, and environmental protection data. Fields cover project code, raw coal indicators, daily processing capacity, energy consumption per unit product, and more. Units mostly use industrial measurement units such as tons, cubic meters, and kilograms of standard coal.

What constraints do these characteristics impose on the knowledge base retrieval and recall link

Coal chemical data includes both structured tables and long-form paragraph text. This requires retrieval systems to support both structured field matching and semantic recall, to avoid information loss from splitting structured content. The update cycles of different data sources differ greatly. The system must support configuring update frequencies by document type, to match retrieval timeliness between real-time production data and static feasibility study reports. Individual project documents have long lengths, leading to extended upload and parsing times. The retrieval system must support resumable uploads and batch task priority configuration, to prevent large documents from blocking the upload queue. The data has a high density of specialized terminology. The retrieval model must ensure accurate recognition of coal chemical-specific terms, to avoid result deviations from generic matching. The system must also support aggregating recall results by project and time dimensions, to meet the multi-dimensional verification needs of due diligence.

How to configure parameters

Configuration Item	Recommended Value	Rationale
`PARSE_FILE_TIMEOUT_SECONDS`	`1200 seconds`	Individual coal chemical feasibility study reports have long lengths, with parsing times far exceeding general documents. 1200 seconds covers the parsing needs of most large documents
`UPLOAD_TASK_PRIORITY_RULE`	`Sort by file size in ascending order`	Coal chemical industry has a large number of large-volume feasibility study reports. Prioritizing small documents reduces user wait times and aligns with the rapid verification needs of due diligence
`RECALL_TOP_K`	`Top 8 entries`	Coal chemical professional data has a high density of specialized terms. Too many recall results increase context redundancy. 8 entries cover core verification dimensions
`SIMILARITY_THRESHOLD`	`0.72–0.78`	Coal chemical specialized terms have high recognition accuracy. A threshold that is too low will introduce irrelevant matches, while a threshold that is too high may miss valid content. This interval can be adjusted slightly based on actual retrieval effects
`STRUCTURED_RECALL_ENABLE`	`Enabled`	Coal chemical data contains a large number of structured parameters. Enabling this feature allows precise matching of fields such as project number and energy consumption indicators, improving retrieval accuracy
`MAX_DOCUMENT_SIZE`	`2000 MB`	Individual coal chemical feasibility study reports can reach hundreds of megabytes in size. 2000 MB covers the needs of most single-document uploads

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. It is recommended to test on your own samples before finalizing settings.

Three common errors

Phenomenon: The system returns a 504 Gateway Timeout error when uploading a single coal chemical feasibility study report larger than 200 MB. Cause: The PARSE_FILE_TIMEOUT_SECONDS parameter was not adjusted, and the default timeout period is insufficient to complete parsing of large documents.
Phenomenon: Uploaded coal chemical documents are not assigned to the specified collection, and cannot be matched during retrieval. Cause: The collection_id and file_id parameters were not passed correctly, resulting in documents being automatically assigned to the default collection.
Phenomenon: When asking general questions unrelated to coal chemical due diligence, the system still returns coal chemical-related content from the knowledge base, and does not trigger the preset irrelevant question response. Cause: The DEFAULT_RESPONSE_WHEN_NO_MATCH parameter was not configured, or the similarity threshold was set to not meet business needs, resulting in recall of low-matching knowledge base content.

How to confirm the configuration is complete

Upload a test coal chemical feasibility study report, check the parse_time field in the parsing log, and confirm that the time does not exceed the configured PARSE_FILE_TIMEOUT_SECONDS value.
After uploading the document, call the collection query interface to verify that the returned collection_id matches the parameter specified during upload.
Submit a retrieval request targeting coal chemical professional parameters, check the score field in the returned results, and confirm that the matching degree falls within the preset SIMILARITY_THRESHOLD interval.
Submit a general question unrelated to coal chemical due diligence, and verify that the system returns a preset irrelevant question response that does not draw content from the knowledge base.

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.