What this category's data looks like
Self-funded study abroad application services involve multilingual materials and terminology processing, with sources including study abroad service contracts, school application forms, personal statements, etc., and the update cadence changes with application rounds and institution requirements. Contract fields include service scope, fees, and signatures; application forms include name, date, education, and signature; personal statements include topic, translated name, and anaphoric reference to the source text. When these materials enter the vector model and indexing feature, contracts and application forms serve as sources of structured fields, personal statements serve as the text source for terminology and parallel drafts, and the indexing service and vector database are only responsible for vectors and index status, and do not generate terminology glossaries or parallel drafts.
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 unified terminology glossary and parallel drafts are then completed by subsequent AI nodes, code nodes, or manual work (retrieval and citation trimming only take supporting materials).
| Object | Check | Verification action |
|---|---|---|
| Study abroad service contract | Name, quantity, date, and signature should be consistent with the application form, and versions need to be synchronized | Check the name, quantity, and date of the same record in the contract and application form; check whether signatures and receipts are complete |
| School application form | Fields, date, and signature should be consistent with the terminology translated names in the personal statement | Open one data row and check the index fields, confirming that multiple vector identifiers for the same group of data are all present |
| Personal statement | The same term is written consistently throughout, and the translated name can refer back to the source text | Sample three terms and check whether their spelling is consistent throughout; verify that the indexing model matches the vector model actually used by the knowledge base |
| Vector and index status | Data row content can be recalled, and the highest score is taken when data in the same group is merged | Run a retrieval once to see whether the same group is merged; after changing models, check the data scope covered by the rebuild task, and trigger only for data that has already been indexed |
Three common errors
- Symptom: duplicate entries appear in retrieval results. Inspect the following: multiple vector identifiers for the same group of data are not merged, or the data row index fields are incompletely recorded.
- Symptom: the name, quantity, and date of the same record do not match between the contract and the application form. Inspect the following: versions are not synchronized, or signatures and receipts are missing.
- Symptom: recall quality drops after changing models. Inspect the following: the rebuild task does not cover all data that has already been indexed, or the indexing model is inconsistent with the vector model actually used by the knowledge base.
How to verify the setup
Acceptance for this feature: sample one data row and check the index fields to confirm that multiple vector identifiers are all present; then run a retrieval once to see whether the same group is merged, and for status values recognize only indexed and rebuild task records.
Business test: sample three terms and check whether their spelling is consistent throughout and whether the translated names can refer back to the source text; record the number of citations by array length, verify the tokens of the cited text separately, and treat limit only as budget references.
- In the knowledge base settings, verify that the indexing model matches the vector model actually used by the knowledge base; open one data row and check whether the index fields record multiple vector identifiers.
- Check the data scope covered by the rebuild task, confirming that after changing models, triggering occurs only for data that has already been indexed; run a retrieval once to confirm that data in the same group is merged and the highest score is taken.