What this category's data looks like
Vocational training subsidy application materials mainly consist of training class filing records, attendance records, and completion assessment forms. The sources are paper or electronic archives submitted by the declaring units, and the update cadence rolls forward with class batches and assessment progress. When these three types of materials enter the vector model and indexing stage, their roles differ: class filing records provide the baseline for institution, trade, headcount, and dates; attendance records provide daily attendance and signature traces; completion assessment forms provide scores, assessment conclusions, and receipts. Field characteristics are concentrated in names, quantities, dates, and signature fields. The names, quantities, and dates of the same record in two materials can easily fail to match. When versions are not synchronized, the old version is still recalled. If signatures or receipts are missing, a complete evidence chain cannot be formed. The indexing service needs to bind each material's vector to the original data identifier so that retrieval can recall by batch and material type, and support subsequent version ledgers and change records.
Configuration and implementation checks
This step is executed by the indexing service and vector database, outputting vectors and index status (whether recall is possible, whether data in the same group is merged). The "version ledger and change records" are then completed by subsequent AI nodes, code nodes, or manual work (retrieval and citation trimming only take supporting materials).
| Object | Check | Verification action |
|---|---|---|
| Index model | Consistent with the vector model actually used by the knowledge base; otherwise recall quality degrades | Check the index model in the knowledge base settings, and review the data range covered by the rebuild task records |
| Index fields of the data row | Multiple vector identifiers for one piece of data are all present; after retrieval, data in the same group is merged by taking the highest score | Open a data row to check the index fields, confirm the status is indexed, then retrieve once more to see whether it is merged |
| Training class filing records | Institution, trade, headcount, and dates match attendance records and completion assessment forms item by item | Compare names, quantities, dates, and signature fields, and check whether the old version is still referenced |
| Completion assessment forms | Scores, assessment conclusions, signatures, and receipts are complete and the version is the current one | Check signatures and receipts, and confirm that citations are updated in sync and the old version remains traceable |
Three common errors
- Symptom: The names, quantities, and dates of the same record in two materials do not match. Inspect the following: Class filing records and attendance records are maintained separately, and versions are not synchronized, causing field conflicts.
- Symptom: Duplicate entries appear in retrieval results. Inspect the following: One piece of data corresponds to multiple vector identifiers, and data in the same group is not merged by taking the highest score, inflating the number of citations.
- Symptom: A data row has content but cannot be retrieved. Inspect the following: After changing the model, rebuild is triggered only for data that has already completed indexing; data rows not covered still remain in the indexing-created state.
How to verify the setup
This feature's acceptance: sample a data row and inspect the index fields to confirm that multiple vector identifiers are all present and the status is indexed, then retrieve once more to see whether the same group is merged and whether the highest score is taken; check whether limit fall within the citation content budget.
Business test: change one piece of content, see whether the version number and citations are updated in sync, and check the number of citations and the tokens of the citation text; array item counts are recorded separately.
- Open a data row to check the index fields, confirm that multiple vector identifiers are all present, and review the data range covered by the rebuild task records.
- Check the index model in the knowledge base settings; after retrieval, check whether data in the same group is merged and whether the tokens of the citation text are within budget, and check
limit.