Internal Office and Employee Services for Property Rights, Asset and State-owned Capital Management: Knowledge Base Retrieval and Recall

What the Data for This Category Looks Like

Data for this category comes from state-owned assets supervision information systems, enterprise asset management systems, property rights exchange systems, appraisal institution reports and financial statements. The update frequency is monthly. Daily documents include property registration forms, asset appraisal reports, property rights transfer plans, on-site transaction announcements, and asset disposal approval forms. Core fields include ownership number, original asset value, appraisal value, transaction base price, and approval circulation nodes. Some documents include physical asset photos and scanned ownership certificates.

What Constraints These Characteristics Impose on Knowledge Base Retrieval and Recall

Monthly updated data requires the knowledge base sync cycle to match the update rhythm. This prevents data lag from affecting core links such as ownership verification and transaction review. Multiple document types include structured fields and scanned documents. Retrieval systems must support cross-format recall, and accurately match core business fields such as ownership number and appraisal value. Data imported from multiple source systems has format differences. A unified preprocessing process must be implemented. At the same time, because error consequences are severe, recall results must guarantee accuracy and completeness. This prevents missing key approval forms or transaction announcements.

Configuration Settings

Reference only; verify against the target FastGPT release and deployment documentation.

| limit | Top 10 entries | Controls the number of single-batch retrieval results, keeps the context length within 4000 tokens, and covers the number of associated documents required for property rights and asset business |

| searchMode | Vector retrieval + keyword hybrid mode | Balances accurate matching of structured fields such as ownership number and appraisal value, and full-text semantic recall capabilities, adapting to multiple types of business documents |

| usingReRank | Enabled | Improves the accuracy of relevance ranking for long documents such as asset appraisal reports and property rights transfer plans, avoids matching deviations caused by truncated long-text semantics |

| datasetSearchUsingExtensionQuery | Enabled | Supplements preconditions such as ownership qualifiers omitted in business questions, optimizes the accuracy of retrieval recall |

| collectionIds | Configured by data source category | Distinguishes asset data from different sources such as state-owned assets supervision systems and property rights exchange systems, facilitating precise recall of documents from specified collections based on business scenarios |

Three Common Misconfigurations

• Phenomenon: Retrieval response times out, the system returns a 504 status code, and background logs show high hard disk read volume. Cause: The number of reranked items is not limited after enabling usingReRank, and the knowledge base segmentation setting is too long. This leads to excessive consumption of reranking computing resources, while increasing hard disk read volume. No optimization was performed for the scenario of multiple long documents in this category.
• Phenomenon: Image file addresses in retrieval results are local paths and cannot be accessed externally. Cause: External storage mapping for knowledge base documents was not configured, and image resources with local server paths were imported directly. File address replacement rules were not adjusted based on business scenarios.
• Phenomenon: Retrieval results do not hit the target property rights transfer plan, and logs show that the model call configuration is inconsistent with the knowledge base configuration. Cause: The model configuration of the application layer and knowledge base layer was not unified. This leads to a mismatch between the actual retrieval model and the preset business-adapted model, affecting recall accuracy.

How to Confirm Configuration Is Correct

• Verify that the FastGPT version is v4.17.0. This can be confirmed via the version information on the system settings page.
• Verify that the value range of similarity meets the core business field matching requirements of this category. This can be verified by testing questions about ownership numbers to check the relevance of recall results.
• Verify that the limit configuration matches the number of associated documents required for the business. This can be tested by batch testing context length and result completeness under different values.
• Verify that collectionIds are configured by data source category. This can be verified by specifying a single data source collection ID to confirm that recall results only include asset documents from the corresponding system.

The values given are common starting points and should be measured 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.