What the documents look like
Rebate calculation happens after sales close, and the object being checked is the policy basis and the financial treatment result. Working materials include the rebate policy, the sales attainment table, the reconciliation statement, and the red-letter invoice. Data sources span ERP sales, dealer remittances, the contract ledger, and the financial system. Monthly or quarterly update cycles mean that at a handover moment different materials may sit at different versions. Citation tracing at this step answers a narrow question: which material, which version, and which state supports a given conclusion or a given handover request.
Rebate disputes and revenue recognition errors frequently trace back to a missing checkable chain between the supporting material and the conclusion. The retrieval layer returns citation content as an array whose length may be zero; an empty array still lets the output path run through. A knowledge base search node may associate one or more knowledge bases that share the same vector model. Knowledge bases with different vector models cannot be associated together. The minimum relevance value is a filter threshold that takes effect only under semantic retrieval or result reranking; it does not perform permission or entity isolation. Reranking requires a model and must be enabled by configuration. Image retrieval requires corresponding image input and model capability. Optional paths drawn in the overall document flow diagram do not mean every request executes all of them.
Constraints at the citation tracing step
A hypothetical drill sample is used here. Material text one reads: "2026 first-quarter dealer rebate policy: attainment rate is calculated on remittance amount, and returns are deducted within the calculation period." Material text two reads: "10 April 2026 reconciliation statement: dealer A, 2026 first-quarter remittance amount 1.2 million, returns 80,000, attainment rate 92%." The draft sentence to be judged reads: "Dealer A's 2026 first-quarter rebate has been calculated and approved for payment." This sentence involves a subject, a period, an amount, and an approval state. The materials do not record an approval conclusion, so the sentence is unsupported.
Three constraints follow. First, an association check: the vector model identifiers of the selected knowledge bases must match before they can be associated together; non-matching ones are excluded and recorded, without executing a cross-model retrieval to compare missed recall. Second, an output check: the search node emits a citation array whose length may be zero, and an empty array does not indicate that the workflow errored out or terminated. Third, a handover check: whether a request, a material, or an operation sits in a particular authorization state cannot be read off a retrieval hit or a form entry. A pending review state does not establish that an operation permission is missing.
Configuration and implementation checks
| Check item | Input | Observed result |
|---|---|---|
| Associated knowledge bases | Vector model identifiers of selected bases | Identifiers must match to associate together; non-matching ones are excluded and recorded |
| Citation content output | Search node output array | Array length may be zero; an empty array does not mean the workflow errored out |
| Citation input handling | Whether retrieval output reaches the answering step | Compare each answer against the cited original text |
| Citation display check | A traceable sample | Use the original text display; do not substitute answer fluency for source evidence |
| Material currency check | Current-version and historical-version documents | Record version differences; whether a citation is adopted still requires review against the effective version |
| Minimum relevance | Semantic retrieval or result reranking setting | This value acts only as a filter threshold; it does not constitute permission or entity isolation |
A hypothetical trial starting value: set minimum relevance to 0.5, on the reasoning that the sample question has a clear subject and short candidate text. The comparison method is to check the same batch of citation entries against two other starting values, 0.3 and 0.7, and observe which entries are added or removed. This value is not an official default.
Three common errors
- Treating a retrieval hit as an authorization basis. Input: the draft sentence "the rebate has been calculated and approved for payment." Comparison object: the reconciliation statement original text. The original text records only remittance amount, return amount, and attainment rate, and does not record an approval conclusion. Observed result: the sentence lacks supporting evidence, and the gap must be recorded.
- Treating a pending review state as a missing operation permission. Input: the handover request "the successor continues processing the unfinished rebate reconciliation." Comparison object: the state field in the material. If the material shows only pending review, the observed result is that the state requires verification, and a permission gap is not inferred.
- Treating a similarity score as a permission filter. Input: the minimum relevance setting value. Comparison object: returned entries against the original subject. Observed result: the score only affects which entries are kept or dropped, and does not exclude unauthorized records. Permission requires a separate system implementation.
How to verify the setup
- Input the hypothetical material text one and text two, compare the subject, period, and amount fields in the draft sentence against the corresponding fields in the originals, and observe that when the originals do not record an approval conclusion the sentence is judged unsupported, with the evidence gap retained.
- Input a paper-level empty array [], compare how the downstream design handles an empty citation, and observe that the output path runs through without error. Do not claim that a particular rule's retrieval necessarily returns an empty array.
- Input two knowledge bases with different vector model identifiers, compare whether the identifiers match, and observe that non-matching ones are excluded and recorded. Do not execute a cross-model retrieval to compare missed recall, and do not infer the runtime result of an association.