What this category of data looks like
State-owned asset management company ledger data comes from four main sources: state-owned assets supervision and reporting systems, internal financial accounting modules, asset disposal approval archives, and property right registration databases.
Two update rhythms apply:
- Real-time incremental updates trigger when daily asset changes occur, such as transfers or scrap.
- Full batch updates trigger during quarterly inventory checks and annual audits.
Each ledger document includes fixed fields: asset number, book value, storage location, usage department, disposal date, and approval document number. Amounts use ten thousand yuan as the standard unit. Quantity units include unit, set, or square meter.
What constraints these characteristics impose on the knowledge base retrieval and recall link
- Use precise identifier matching for retrieval to avoid ambiguity from fixed-format fields.
- Configure the retrieval system to support both real-time incremental synchronization and full batch updates, to match the combined update rhythm.
- Adjust retrieval rules specifically, because general semantic retrieval will produce irrelevant hits when paired with exclusive industry terminology and fixed fields.
- Limit the number of recalled entries per single retrieval, since single ledger entries are small but total data volume is large, to avoid context overflow.
How to Set Up Configuration
Reference only; verify against the target FastGPT release and deployment documentation.
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
similarity | 0.75–0.85 | State-owned asset management ledgers require precise matching of core fields such as asset numbers and approval document numbers. This range filters irrelevant hits while retaining valid recall results |
limit | Top 10 entries | Too many recalled entries per single retrieval increases context processing pressure. 10 entries can cover the core needs of a single ledger summary task |
searchMode | Exact match mode | Ledgers contain structured fields such as asset numbers with fixed prefixes. Exact matching avoids ambiguous recall |
usingReRank | Enabled | Recall results must be sorted by relevance to ensure core asset entries are prioritized for extraction in summary reports |
datasetSearchUsingExtensionQuery | Enabled | Ledgers use exclusive state-owned assets industry terminology. Question extension can cover more relevant entries |
collectionIds | Collection ID corresponding to the state-owned asset ledger knowledge base | Restrict retrieval scope to only state-owned asset management ledger data, avoiding mixing irrelevant documents |
Three Common Misconfigurations
- Phenomenon: Retrieval returns many irrelevant asset entries for ledger summary, even with a valid
similarityrange. Cause: Exact match mode is disabled, so general semantic retrieval causes ambiguous matches for asset numbers and approval document numbers. - Phenomenon: The interface shows field mismatch or synchronization failure when importing ledger data from MySQL. Cause: MySQL fields are not mapped to required ledger fixed fields, and incremental update trigger rules are not configured.
- Phenomenon: Retrieved results are far fewer than expected, missing required asset ledger entries. Cause: Question extension query is disabled, so industry terminology variants are not covered, leading to missed recall.
How to Confirm Configuration Completion
- Manually enter a known asset number, then check if the corresponding ledger entry appears first in retrieval results.
- Trigger a ledger summary task, then verify that the number of recalled entries matches the preset
limitvalue. - Check the knowledge base collection’s update log, then confirm that scheduled incremental updates run at the preset rhythm.
- Enter a query with state-owned assets industry terminology, then check if corresponding asset entries are recalled.
The values provided 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.