What data for this category looks like
State-owned industrial fund data is primarily sourced from state-owned assets supervision and reporting systems, fund manager operational ledgers, post-investment project management archives, and fiscal appropriation vouchers. Update cadence follows monthly basic ledger updates, quarterly operational summary updates, and annual performance report updates. Temporary project contributions and exit changes are synced in real time. Most individual documents are structured tables, containing fields such as fund entity name, investor type, subscribed amount, paid-in progress, investment project list, exit proceeds, and shareholding ratio. Amount units are typically ten thousand yuan or hundred million yuan. Time units use natural months and years. Shareholding ratio is expressed as a percentage value.
Constraints imposed by these characteristics on knowledge base retrieval and recall
The structured data characteristics of state-owned industrial funds require retrieval to prioritize precise field matching. Generic full-text retrieval logic must be avoided to prevent mixing in irrelevant fiscal policy documents. The monthly high-frequency update characteristic requires the knowledge base synchronization cycle to match the update rhythm. Mismatched cycles will result in data lag. Ledger content associated with multiple fields requires the retrieval system to support combined field filtering. For example, matching both fund name and investment time. The number of items in a single batch retrieval must be reasonably controlled. Uncontrolled volume will exceed the context window and cause report generation truncation.
How to set the configuration
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
similarity | 0.72–0.88 | State-owned industrial fund ledgers have clear field matching rules. A threshold that is too low will mix in irrelevant fiscal policy documents, while a threshold that is too high will miss some ledger entries that meet the required relevance level |
limit | Top 8–12 entries | A single ledger aggregation needs to cover up to 10 core fund projects. Too many retrieval results will exceed the context window and affect the coherence of report generation |
usingReRank | Enabled | Ledger data has high field association strength. The re-ranking function can reorder results based on semantic association, improving the display priority of entries matching core fields |
datasetSearchUsingExtensionQuery | Enabled | State-owned industrial funds have a large number of exclusive terms, such as "paid-in capital amount" and "annualized exit return rate". Extended queries can cover synonyms and near-synonyms of terms, expanding retrieval recall scope |
searchMode | hybrid | Combine vector retrieval and field matching, balancing semantic association and precise field matching, adapting to the structured and semi-structured mixed data characteristics of ledgers |
collectionIds | Exclusive dataset ID for state-owned industrial funds | Limit the retrieval scope to only the ledger data of this category, avoiding mixing in knowledge base content from other categories |
Three common misconfigurations
- Retrieval results include a large number of documents unrelated to fund ledgers. This occurs when the
collectionIdsparameter is not set to the state-owned industrial fund exclusive dataset, allowing the retrieval scope to cover knowledge base content from other categories. - The latest monthly ledger update data cannot be recalled during queries. This happens when the knowledge base incremental synchronization cycle is set to weekly, which does not match the monthly update rhythm of ledgers. The latest data will not be synced to the retrieval library in a timely manner.
- Retrieval result relevance is low, and some correct paid-in progress entries are not ranked at the top. This is caused by not enabling the
usingReRankfunction. Relying only on the initial ranking of basic vector retrieval fails to reflect the priority of field association.
How to confirm the configuration is properly set
- Log in to the FastGPT v4.17.0 knowledge base management backend. View the synchronization logs of the corresponding dataset to confirm that the monthly ledger incremental synchronization task is triggered and completed daily.
- Enter the test query "paid-in progress of a certain state-owned industrial fund in the first half of 2024". Check whether the returned results include accurate entries for core fields such as the paid-in amount and progress percentage of the corresponding fund.
- Access the retrieval configuration panel. Confirm that
usingReRankanddatasetSearchUsingExtensionQueryare both enabled, and thesimilaritythreshold is set within the 0.72–0.88 range. - Test batch retrieval of 10 ledger entries from different funds. Confirm that the number of returned entries per single request is within the 8–12 range, and no truncation occurs due to exceeding the context window.
The values provided here are common starting points and should be evaluated against the user'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.