What this category's data looks like
This page addresses primary and secondary school timetable and after-school service scheduling scenarios. The materials come from the master timetable, teacher assignment table, after-school service project table, and their multilingual parallel versions. The master timetable provides class, week, period, and course name; the teacher assignment table provides assigned teacher, subject, and number of class hours; the after-school service project table provides project name, number of participants, date, and signed receipt. Materials are updated by semester or month, and common fields include course name, teacher name, project name, number of people, date, version number, and signature field. During multilingual materials and terminology processing, the master timetable and teacher assignment table are used to establish course and subject terminology alignment, while the after-school service project table is used to establish project name and receipt terminology alignment. The three materials together enter the vector model and indexing stage, serving as supporting materials for subsequent retrieval and citation trimming.
Configuration and implementation checks
This step is executed by the indexing service and vector database, outputting vectors and index status (whether recall is possible and whether data in the same group is merged). The unified terminology table and parallel versions are then completed by subsequent AI nodes, code nodes, or manual work (retrieval and citation trimming only take supporting materials).
| Object | Check | Verification action |
|---|---|---|
| Master timetable | Check class, week, period, course name, and version number; the same course name is written consistently throughout, and the translated name can refer back to the original text | Open one master timetable data row, check whether its index field records multiple vector identifiers, and run a retrieval to see whether data in the same group is merged |
| Teacher assignment table | Check teacher name, subject, number of class hours, and signature field; the name, quantity, and date of the same record match between the master timetable and the teacher assignment table | In the knowledge base settings, check whether 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 |
| After-school service project table | Check project name, number of participants, date, version number, and receipt signature; when the name, quantity, and date of the same project do not match between the two materials, record the discrepancy | Open one after-school service project table data row, check whether the index field is complete, and run a retrieval to see whether data in the same group can be recalled and merged |
Three common errors
- Symptom: the same course name is written differently in the master timetable and the teacher assignment table. Inspect the following: multilingual material terminology is not unified and versions are not synchronized, causing the name, quantity, and date of the same record to fail to match.
- Symptom: the after-school service project table lacks a signature or receipt. Inspect the following: the signature field was not completed during material circulation, versions were not synchronized, and the published draft is inconsistent with the source material.
- Symptom: duplicate entries appear in retrieval results. Inspect the following: the same group of data corresponds to multiple vector identifiers, the highest score was not taken during merging, or after changing models, rebuild was triggered only for data that had already completed indexing.
How to verify the setup
This feature acceptance: sample one data row and inspect the index field to confirm that multiple vector identifiers for one piece of data are all present, then run a retrieval to see whether data in the same group is merged; the index model is consistent with the vector model actually used by the knowledge base; after changing models, rebuild is triggered only for data that has already completed indexing; check the status values indexed and the rebuild task record; the tokens and array count of the cited text are recorded separately; limit are checked against the citation content budget.
Business test: sample three terms and check whether their spelling is consistent throughout; the same term is consistent throughout, and the translated name can refer back to the original text.
- Open one data row and check the index field to confirm that multiple vector identifiers are all present, and in the knowledge base settings check that the index model is consistent with the vector model actually used by the knowledge base.
- View the data scope covered by the rebuild task, confirm that after changing models it is triggered only for data that has already completed indexing, and check indexed and the rebuild task record.