What this category's data looks like
In the compulsory education dropout prevention and retention scenario, multilingual materials and terminology processing mainly deals with three types of materials: dropout risk ledgers, persuasion-to-return records, and home visit records. Ledger fields include student identifier, risk level, persuasion-to-return status, responsible person, and date; persuasion-to-return records include persuasion method, subject, time, and receipt; home visit records include visit date, participants, and signature. The materials are submitted by schools and townships, and the update cadence rolls forward with the semester and persuasion-to-return progress. When entering the model access and configuration stage, the ledger serves as the terminology anchor, the persuasion-to-return records serve as the translation-name cross-reference, and the home visit records serve as the signature and receipt verification. The multilingual comparison draft requires the same terminology to be consistent throughout the entire text, translation names to be traceable back to the source text, and the dates, quantities, and signatures in the fields to be aligned item by item between the two materials.
Configuration and implementation checks
This stage 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 dialogue and retrieval using that model. Models are divided into five categories: language, indexing, reranking, speech synthesis, and speech recognition, and different stages bind different model types.
| Object | Check | Verification action |
|---|---|---|
| Dropout risk ledger | The name, quantity, and date of the same student identifier, risk level, and persuasion-to-return status must be consistent between the ledger and the persuasion-to-return records | Check the fields and dates of the two materials, the ledger and the persuasion-to-return records, and compare the model identifier with the model name returned by the channel |
| Persuasion-to-return records | The persuasion method, subject, time, and receipt must correspond to the home visit records; missing signature or receipt is regarded as incomplete | Extract three terms and check their spelling throughout the entire text, check the receipt and signature columns, and check whether maxContext and maxTokens satisfy long-text comparison |
| Home visit records | The visit date, participants, and signature must align with the ledger dates; when versions are not synchronized, the latest signed draft prevails | Check the home visit records against the ledger dates and signatures, check whether quoteMaxToken covers the tokens of the quoted text, and record the array count separately |
| Model configuration | The five model categories—language, indexing, reranking, speech synthesis, and speech recognition—correspond to the stages in which they are used | In the model configuration, check the type labels, compare them with the channel configuration and key source, and confirm that the model identifier is consistent with the name listed in the documentation |
Three common errors
- Phenomenon: The name, quantity, and date of the same student do not match between the ledger and the persuasion-to-return records. Cause: The two materials are updated separately, versions are not synchronized, and terminology traceback validation is not performed at entry.
- Phenomenon: Home visit records lack a signature or receipt, and the externally released draft cannot confirm responsibility. Cause: The signature column check is not set up in the material circulation stage, and receipts are not archived together with the records.
- Phenomenon: Retrieval reports an indexing model-related error, or the answer style changes abruptly after switching models. Cause: The indexing stage is bound to a language model, and the model identifier is inconsistent with the name listed in the documentation.
How to verify the setup
This feature acceptance: run one dialogue and one retrieval, check the model identifier in the response, confirm that the language and indexing models are bound to their corresponding stages respectively, and check the value sources of maxContext, maxTokens, quoteMaxToken, and toolChoice.
Business test: extract three terms and check whether their spelling is consistent throughout the entire text, check whether the translation names can be traced back to the source text, and compare the dates, quantities, and signatures of the ledger, persuasion-to-return records, and home visit records.
- In the model configuration, check item by item the type labels of the five model categories—language, indexing, reranking, speech synthesis, and speech recognition—and confirm that they correspond to the stages in which they are used.
- Compare with the channel configuration and key source, check that the model name returned by the channel is consistent with the model identifier listed in the documentation, and avoid retrieval reporting an indexing model-related error.