Vector Models and Indexes for Off-Campus Training Registration and Compliance: Handle Multilingual Materials and Terminology

Training Compliance: review vector indexes for multilingual work. Check source versions, input mappings and the values received by downstream nodes.

What this category's data looks like

For off-campus training compliance filing and penalty response, materials usually come from three categories: school operating licenses, course filing materials, and fee disclosure, updated by semester or inspection checkpoint. School operating licenses contain institution name, address, validity period, and signature; course filing materials contain course name, class hours, instructor, and date; fee disclosure contains items, amounts, refund rules, and receipts. When the three material categories enter this feature, their roles differ: school operating licenses and course filing materials serve as terminology sources, while fee disclosure serves as terminology use cases, jointly supporting retrieval and citation trimming for the unified terminology table and comparison drafts. In terms of field characteristics, the name, quantity, and date of the same record often do not match across the two materials, versions are not synchronized, and signatures or receipts are missing. Multilingual materials and terminology handling require the same term to be consistent throughout the entire text, translated names to be traceable back to the source text, and the index to cover multilingual text and terminology comparison segments.

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 comparison drafts" are then completed by subsequent AI nodes, code nodes, or manual work (retrieval and citation trimming only take supporting materials). The indexing model must be consistent with the vector model actually used by the knowledge base. The index field of a data row records multiple vector identifiers. Retrieval first recalls vectors and then merges them back into the original data by identifier, taking the highest score for the same group of data.

ObjectCheckVerification action
School operating licenseWhether the institution name, address, validity period, and signature are consistent with the course filing materials and fee disclosure, and whether dates and quantities matchOpen a data row and check whether the index field contains multiple vector identifiers, then run a retrieval to see whether the same group is merged; check the license name against the fee disclosure name, and the course filing material date against the license validity period
Course filing materialsWhether the course name, class hours, instructor, and date are consistent with the school operating license and fee disclosure, and whether versions are synchronizedIn the knowledge base settings, check whether the indexing model is consistent with the vector model actually used by the knowledge base; view the data scope covered by the rebuild task and confirm that after changing the model, it is triggered only for data whose indexing has already been completed; check the class hours and dates in the course filing materials against the fee disclosure
Fee disclosureWhether the fee items, amounts, refund rules, and receipts are consistent with the school operating license and course filing materials, and whether signatures or receipts are missingOpen a data row and check whether the index field contains multiple vector identifiers; run a retrieval to see whether the same group is merged; check the fee disclosure receipt signature against the school operating license signature, and the course filing material date

Three common errors

  • Phenomenon: The same institution name is written differently in the school operating license and fee disclosure, and two records are recalled during retrieval. Inspect the following: The name of the same record does not match across the two materials, and the index field has not merged data in the same group.
  • Phenomenon: The class hours in the course filing materials do not match the fee disclosure, and citation trimming takes the old version. Inspect the following: Versions are not synchronized, and the rebuild task does not cover the data scope whose indexing has already been completed.
  • Phenomenon: The fee disclosure lacks a signature or receipt, and duplicate entries appear in retrieval results. Inspect the following: Material fields are incomplete, data rows have content but cannot be retrieved, and the indexing model is inconsistent with the vector model actually used by the knowledge base.

How to verify the setup

This feature's acceptance check: sample one data row and inspect the index field to confirm that defaultToken and maxToken are consistent with the indexing model, then run a retrieval to see whether the same group is merged; for status values, recognize only indexed and rebuild task records.

Business test: sample three terms and check whether their wording is consistent throughout the entire text, verify whether translated names can be traced back to the source text, record the number of citations by array length, and separately check tokens for quoteMaxToken as the citation content budget.

  • In the knowledge base settings, check that the indexing model is consistent with the vector model actually used by the knowledge base, view the data scope covered by the rebuild task, and confirm that after changing the model, it is triggered only for data whose indexing has already been completed.
  • Open a data row and check whether the index field contains multiple vector identifiers, run a retrieval to see whether the same group is merged, and check limit against the number of citations and the budget record for quoteMaxToken.