What this category's data looks like
This page addresses multilingual materials and terminology handling for enterprise sales product training. The materials come from three sources: product manuals, sales conversation scripts, and channel training schedules. Product manuals provide the original terminology and field definitions, sales conversation scripts carry translated names and anaphoric references, and channel training schedules record course dates, quantities, and signed receipts. Updates proceed by version batch, and the field characteristics center on terminology names, translated names, version numbers, dates, quantities, and signature fields. When materials enter the vector model and indexing stage, manuals and scripts are stored as source data in business database data tables, each generating vector identifiers and writing them into the index field; schedules participate as reference materials in same-group recall. The three types of materials play different roles in the index: manuals and scripts are used for recall and merging, while schedules are used to check whether the names, quantities, and dates of the same record are consistent across multiple materials, as well as whether versions are synchronized and signatures or receipts are complete.
Configuration and implementation checks
This stage is executed by the indexing service and the vector database, outputting vectors and index status (whether recall is possible and whether same-group data is merged). The "unified terminology table and comparison draft" is then completed by subsequent AI nodes, code nodes, or humans (retrieval and citation trimming only take supporting materials). Vectors are stored in the vector database, source data is stored in data tables in the business database, and the index field records the corresponding multiple vector identifiers; retrieval first recalls vectors, then merges back to the source data by identifier, and the highest score is taken for the same group of data.
| Object | Check | Verification action |
|---|---|---|
| Index model | Consistent with the vector model actually used by the knowledge base; after changing the model, rebuild is triggered only for data that has already been indexed, and the status value shows indexed and the rebuild task record | Check the index model in the knowledge base settings and view the data scope covered by the rebuild task |
| Index field of the data row | Multiple vector identifiers for one piece of data are all present; the reference text budgets corresponding to limit do not affect the array count record | Open a data row and check the index field to confirm that multiple vector identifiers are complete |
| Product manuals and sales conversation scripts | The same terminology is consistent throughout, and translated names can refer back to the original text; the names, quantities, and dates of the same record match across the two materials, and versions are synchronized | Sample three terms and check whether their usage is consistent throughout; compare the fields, dates, and signatures of the manuals and scripts |
| Channel training schedules | Course dates, quantities, and signed receipts are complete, and consistent with the version numbers of the manuals and scripts | Check the names, quantities, and dates of the schedules against the manuals and scripts, and inspect signatures or receipts |
Three common errors
- Symptom: duplicate entries appear in retrieval results. Inspect the following: the same group of source data corresponds to multiple vector identifiers, and merging did not consolidate by highest score, or the index field record is incomplete.
- Symptom: recall quality drops after changing the model. Inspect the following: rebuild is triggered only for data that has already been indexed, does not cover all data rows, and versions are not synchronized.
- Symptom: a data row has content but cannot be retrieved. Inspect the following: the index field is missing vector identifiers, or the row has not completed indexing and its status has not reached indexed.
How to verify the setup
This feature's acceptance: sample a data row to see whether the index field records multiple vector identifiers, then retrieve once to see whether same-group data is merged and whether the vector score takes the highest score; for status values, only indexed and the rebuild task record are recognized.
Business test: sample three terms and check whether their usage is consistent throughout, confirm that translated names can refer back to the original text, and check the fields, dates, and signatures of the manuals, scripts, and schedules.
- In the knowledge base settings, check that the index model is consistent with the vector model actually used by the knowledge base, and view the data scope covered by the rebuild task.
- Open a data row and check the index field to confirm that under the reference text budgets corresponding to
limit, multiple vector identifiers are all present and the array count is recorded separately.