Vector Models and Indexes for Kindergarten Operations and Quality Self-Assessment: Handle Multilingual Materials and Terminology

Kindergarten Quality: 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

This page addresses the scenario of kindergarten operation behavior and quality self-assessment. Materials include self-assessment reports, issue lists, rectification plans, as well as multilingual terminology glossaries and comparison drafts. Sources are mostly self-filled by kindergartens, supervision receipts, and translated drafts, with update cadence rolling along assessment cycles and rectification milestones. Field characteristics center on record names, quantities, dates, and signature fields; the same record often appears with different wording across two materials. When materials enter this feature, self-assessment reports and issue lists serve as the original texts to be retrieved, rectification plans and comparison drafts serve as the basis for comparison, and terminology glossaries and comparison drafts are used to unify translated names and refer back to the original text.

Configuration and implementation checks

This step is executed by the indexing service and vector database, outputting vectors and index status (whether recall is possible, whether data in the same group is merged). "Unify terminology glossaries and comparison drafts" is then completed by subsequent AI nodes, code nodes, or manual work (retrieval and citation trimming only take supporting materials).

ObjectCheckVerification action
Self-assessment reportThe name, quantity, and date of the same record do not match across the two materials, and the signature field and receipt are missingOpen a data row to check the index fields, confirm that multiple vector identifiers are all present, then retrieve once more to see whether the same group is merged
Issue listVersions are not synchronized, the same term is written inconsistently throughout, and the translated name cannot refer back to the original textIn the knowledge base settings, check whether the index model and the vector model actually used by the knowledge base are consistent
Rectification planDates and signatures do not match between the rectification plan and the self-assessment report, and the receipt has not been archivedCheck the data scope covered by the rebuild task; after changing models, trigger only for data whose indexing has already been completed
Terminology glossary and comparison draftThe same term is written inconsistently throughout; sample three terms to check whether their wording is consistent throughoutCheck whether the data row status is indexed, and view the rebuild task records

Three common errors

  • Symptom: duplicate entries appear in retrieval results. Inspect the following: the same group of original data corresponds to multiple vector identifiers, and merging did not consolidate by the highest score; the name and quantity are each written differently in the two materials.
  • Symptom: recall quality drops after changing models. Inspect the following: the rebuild task only; data rows whose indexing has not been completed do not participate in recall, so indexing must be completed before rebuilding.
  • Symptom: a data row has content but cannot be retrieved. Inspect the following: index fields are missing or vector identifiers were not written; materials lacking signatures or receipts did not enter the index, and translated term names cannot refer back to the original text.

How to verify the setup

This feature's acceptance: sample one data row to check the index fields, then retrieve once more to see whether the same group is merged; for status values, only indexed and rebuild task records are recognized; when citation limits are involved, check the tokens of the cited text; array item counts are recorded separately; limit, and quoteMaxToken are checked against their respective budgets.

Business test: sample three terms to check whether their wording is consistent throughout, confirm that the same term is consistent throughout and that translated names can refer back to the original text.

  • Open a data row to check the index fields, confirm that multiple vector identifiers for one data item are all present, and view the rebuild task records.
  • In the knowledge base settings, check that the index model is consistent with the vector model actually used by the knowledge base, then retrieve once more to see whether the same group is merged.