What this category's data looks like
This page addresses multilingual materials and terminology handling in the scenario of student awards, grants, loans, and hardship determination. Material sources include three types: family economic hardship determination forms, award and grant application forms, and loan receipts. The determination form contains fields such as family members, income, and hardship level; the application form contains student ID, department, award name, amount, and signature; the loan receipt contains contract number, disbursement date, and receipt seal. The three types of materials have different update rhythms: the determination form is adjusted by academic year, the application form is submitted by batch, and the receipt is returned according to disbursement progress. When materials enter this function, the determination form and application form serve as corpus for terminology extraction and the comparison draft, and the receipt serves as the verification basis for translated names referring back to the source text; the unified terminology table and comparison draft are then completed by subsequent AI nodes, code nodes, or manual work, and before external release it is necessary to ensure that the same terminology is consistent throughout the entire text and that translated names can refer back to the source text.
Configuration and implementation checks
This step is executed by the server-side model channel configuration, outputting model binding relationships and channel responses. The "unified terminology table and comparison draft" are then completed by subsequent AI nodes, code nodes, or manual work. Models are divided into five categories: language, indexing, reranking, speech synthesis, and speech recognition. Different steps bind different model types, and during configuration they are labeled according to the corresponding type for the step.
| Object | Check | Verification action |
|---|---|---|
| Family economic hardship determination form | Field names, quantity, and date must be consistent with the same record in the award and grant application form | Verify whether the name, family population, and determination date wording in the determination form and application form are consistent, and compare against the model name returned by the channel |
| Award and grant application form | Award name, amount, and signature must be able to refer back to the same record as the loan receipt | Verify whether the contract number, disbursement date, and seal in the application form and receipt match, and check the values of maxContext and maxTokens |
| Loan receipt | Receipt number, disbursement date, and signature or seal must be complete and version-synchronized | Verify whether the receipt is missing a signature or receipt, and check whether quoteMaxToken and toolChoice are configured according to the step |
| Model type | Corresponds to the step to be used | Check the type label in the model configuration and compare against the model name returned by the channel |
Three common errors
- Symptom: The family population quantity for the same student does not match between the determination form and the application form. Cause: The two materials were entered separately, and name and quantity reference back to the same record was not performed.
- Symptom: The disbursement date on the loan receipt is inconsistent with the batch date on the application form. Cause: The version was not synchronized, and the application form was not written back after the receipt was updated.
- Symptom: Retrieval reports an indexing model-related error or authentication failure. Cause: The channel and key are inconsistent with the connected service, or the model identifier does not match the name listed in the documentation.
How to verify the setup
This function's acceptance: run one conversation and one retrieval, check the model identifier in the response, and confirm that the language model and indexing model are bound to the corresponding steps respectively.
Business test: sample three terms to check whether their wording is consistent throughout the entire text, and verify whether the translated names can refer back to the source text.
- Check the channel configuration and key source, and confirm that the model identifier matches the name listed in the documentation.
- Check the model type labels by step, and confirm that language, indexing, reranking, speech synthesis, and speech recognition are each bound correctly.