Vector Models and Indexes for Adult College Entrance Applications and Admissions: Handle Multilingual Materials and Terminology

Adult Admissions: 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

Adult college entrance examination registration and admission management involves three types of materials: registration forms, care bonus point materials, and admission rosters. The sources are admissions examination institutions, registration points, and institutions, and the update rhythm advances with registration, review, and admission batches. Registration forms contain the candidate's basic information, application level, and subject category; care bonus point materials contain the certificate type, issuing unit, and date; admission rosters contain the candidate number, admitted major, and signature field. When these three types of materials enter the vector model and indexing stage, the registration form serves as the main record and provides the field baseline, care bonus point materials serve as attachments and provide supporting fields, and the admission roster serves as the result record and provides final-state fields. The name, quantity, and date of the same candidate in the registration form and admission roster must be comparable, and signatures and receipts must be traceable. Multilingual materials and terminology processing require the same term to be consistent throughout the entire text and the translated name to be able to refer back to the original text, and the vector model and indexing must support this kind of comparative retrieval.

Configuration and implementation checks

This stage is executed by the indexing service and vector database, and outputs vectors and index status (whether recall is possible and whether data in the same group is merged). The "unified terminology table and comparison draft" is then completed by subsequent AI nodes, code nodes, or manual work (retrieval and citation trimming only take supporting materials). The indexing model is consistent with the vector model actually used by the knowledge base, and the index field of a data row records multiple vector identifiers for one piece of data.

ObjectCheckVerification action
Adult college entrance examination registration formThe name, quantity, and date of the same candidate in the registration form and admission roster must be consistent, and signatures and receipts must be completeOpen a data row and check the index field to confirm that multiple vector identifiers are all present; check the indexing model in the knowledge base settings
Care bonus point materialsThe certificate type, issuing unit, and date of the same record in the registration form and care bonus point materials must match, and versions must be synchronizedCheck the data scope covered by the rebuild task and confirm that after changing the model, rebuild is triggered only for data that has already been indexed; check the status value indexed and the rebuild task record
Admission rosterThe candidate number, admitted major, and signature field of the same candidate in the admission roster and registration form must be consistent, and missing signatures or receipts must be markedSample a data row to look at the index field, then retrieve once to see whether the same group is merged; record the number of citations and the tokens of the cited text, and check quoteMaxToken separately as the citation content budget
Data row index fieldMultiple vector identifiers for one piece of data are all present, and during retrieval they are merged back to the original data by identifier, with the highest score taken for the same group of dataCheck the values of defaultToken and maxToken in the indexing and retrieval stages; confirm that duplicate entries do not appear after the same group of data is merged

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 field is missing some vector identifiers.
  • Symptom: the name, quantity, and date of the same record in the registration form and admission roster do not match. Inspect the following: versions are not synchronized, and after the two materials are updated separately, they are not checked back against the original text.
  • Symptom: care bonus point materials lack signatures or receipts, and the signature field in the admission roster is empty. Inspect the following: the receipt status is not recorded during the material circulation stage.

How to verify the setup

Acceptance for this feature: sample a data row to look at the index field and confirm that multiple vector identifiers are all present; then retrieve once to see whether the same group is merged, and for status values only recognize indexed and the rebuild task record.

Business test: sample three terms and check whether their spelling is consistent throughout the entire text, and whether the translated names can refer back to the original text; record the number of citations and the tokens of the cited text, and check quoteMaxToken separately 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, and after changing the model, check the data scope covered by the rebuild task.
  • Open a data row and check the index field to confirm that multiple vector identifiers for one piece of data are all present; check the values of defaultToken and maxToken in the indexing and retrieval stages.