What this category's data looks like
This page addresses the journal three-review three-proof and editorial quality scenario. Materials include three-review forms, proofs, proofreading records, and multilingual materials and terminology comparison drafts. Sources are the various stages of the editorial process and translation-proofing checkpoints, and the update cadence advances with review rounds and proofing rounds. Field characteristics center on record names, quantities, dates, and signature receipts. When these materials enter the vector model and indexing function, they serve only as raw data to be processed and as index text sources. The indexing service and vector database output vectors and index status. The unified terminology table and comparison draft are subsequently completed by AI nodes, code nodes, or manual work. The same term's spelling, translated name, and original-text anaphoric relationship across different materials depend on the multiple vector identifiers recorded in the index field of the data row. During retrieval, vectors are first recalled, then merged back to the original data by identifier, with the highest score taken within the same group, providing supporting material for the subsequent unified terminology table and comparison draft.
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). The "unified terminology table and comparison draft" is subsequently completed by AI nodes, code nodes, or manual work (retrieval and citation trimming take only supporting material). 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 for one piece of data. After changing models, rebuild is triggered only for data that has already been indexed.
| Object | Check | Verification action |
|---|---|---|
| Three-review form | Check whether the name, quantity, date, and signature receipt correspond item by item with the proofs and proofreading records; the same record must not appear with different spellings in two materials | Open a data row and check whether the index field contains multiple vector identifiers, confirm that the text slices corresponding to defaultToken and maxToken are both indexed, and that the status is indexed |
| Proof | Check whether the versions are synchronized, whether the same term is spelled consistently throughout, whether the translated name can refer back to the original text, and whether missing signatures or receipts must be marked | In the knowledge base settings, check that the indexing model is consistent with the vector model actually used, view the data scope covered by the rebuild task record, and confirm that the slices for defaultToken and maxToken are not omitted |
| Proofreading record | Check whether dates and signatures are complete, whether the name, quantity, and date of the same record match across the two materials, and whether unsynchronized versions must be rolled back | Run a retrieval to see whether data in the same group is merged. If duplicate entries appear, check whether the index field of the data row completely records multiple vector identifiers, and check the rebuild task record |
| Multilingual materials and terminology comparison draft | Check that the same term is spelled consistently throughout and that the translated name can refer back to the original text; sample three terms to check whether the spelling is consistent throughout | Open a data row and check the index field, confirm that the slices for defaultToken and maxToken both generate vectors and that the status is indexed; after changing models, trigger rebuild only for data that has already been indexed |
Three common errors
- Symptom: The name, quantity, and date of the same record do not match between the three-review form and the proofreading record. Inspect the following: The two materials each enter a data row, During retrieval.
- Symptom: Recall quality drops after changing models. Inspect the following: The rebuild task record covers only data that has already been indexed. Data rows that cannot be rebuilt do not participate in recall. Indexing must be completed first, and versions are not synchronized and lack confirmation of signature receipts.
- Symptom: A data row has content but cannot be retrieved. Inspect the following: The index field does not completely record multiple vector identifiers, or the indexing model is inconsistent with the vector model actually used by the knowledge base, so vectors cannot be recalled.
How to verify the setup
Acceptance for this function: sample a data row and inspect the index field, confirm that the slices for defaultToken and maxToken both generate vectors and that the status is indexed, then run a retrieval to see whether the same group is merged. If duplicates appear, check the rebuild task record.
Business test: sample three terms to check whether the spelling is consistent throughout, check whether the translated names can refer back to the original text, and check whether the dates and signatures of the three-review forms, proofs, and proofreading records are complete.
- Open a data row, check whether the index field records multiple vector identifiers, confirm that the slices for
defaultTokenandmaxTokenare both indexed, and that the status is indexed. - View the data scope covered by the rebuild task record. After changing models, trigger rebuild only for data that has already been indexed, and check that the indexing model is consistent with the vector model actually used by the knowledge base.