What the documents look like
A brand dealer ordering event is built around offline dealer reservations. It does not directly manage platform storefronts. The working materials are the ordering handbook, the ordering contract, the sample list and the credit approval record. The main data comes from the ordering event system, historical sales, dealer inventory and financial credit. The update rhythm is quarterly and annual.
For cross-border materials and multilingual retrieval, one ordering handbook can exist in a Chinese version and an English version at the same time. Dealer-submitted order quantities and credit applications need to correspond clause by clause with the correct version. The citation tracing step has one central job: whether a clause, quantity or status that appears in an answer can be traced back to a specific document and a specific version.
This category differs from platform multi-store matrix management. The retrieval scope is the selected knowledge base and its material versions, not storefront operations. Only knowledge bases that share the same vector model can be associated together. Semantic retrieval and the minimum relevance score perform similarity filtering. They do not perform permission isolation or entity isolation. Hybrid retrieval merges multiple result paths through RRF. The rerank model produces a 0-1 score used for filtering. None of these change the requirement that a citation must be traceable.
Constraints at the citation tracing step
The knowledge base search node outputs a citation content array, and the length can be zero. When no content is found, that output path still runs through. This means an empty citation array is not by itself a workflow error, and it is not an approval, an authorization or a completed business action.
The overall retrieval process combines text, images, semantic recall, full-text recall, question optimization and reranking, then merges the multiple result paths into citation content. The optional paths shown in the overall flow diagram do not mean every request executes all of them. Image retrieval requires a corresponding image input and model capability. Reranking requires an available model and must be enabled according to the settings. RRF is a merge process for hybrid results, not a switch that is turned on.
The minimum relevance score is a filtering threshold, not a final sorting rule. It is not a category filter, an entity filter or a permission filter. A similarity setting does not exclude unrelated businesses or unauthorized records. Retrieval is not authorization.
Assume a paper exercise sample. A brand channel department holds a Chinese version of an ordering handbook and an English version. Section 3 of the Chinese version states: "The deposit is payable within 7 days after order confirmation at this ordering fair." (English rendering) The corresponding paragraph in the English version states: "deposit due within 7 days after order confirmation." Dealer A's credit approval status is recorded in the system as "pending review" (English rendering). A draft sentence reads: "Dealer A's credit has been approved and the order can be placed under the payment terms in Section 3 of the ordering handbook." The question to decide is whether this draft sentence is consistent with the materials above.
The draft sentence names a subject (Dealer A), an object (credit approval), a status (approved) and a scope (ordering under Section 3). The system status field records "pending review." These are two mutually exclusive values in the same field for the same subject and the same period. The draft sentence is therefore not supported by the available evidence. The pending status does not prove that operation permission is absent, and it is not a completed approval.
Configuration and implementation checks
| Configuration item | Hypothetical starting point for this exercise | Reason and comparison method |
|---|---|---|
| Associated knowledge bases | Chinese handbook library and English handbook library | Check whether the two vector model identifiers are the same; exclude any that differ and do not run a cross-model comparison |
| Search mode | Hybrid retrieval | The handbook contains numbers and proper nouns; compare recall coverage against semantic retrieval results |
| Minimum relevance | 0.5 | Hypothetical starting point; compare the number of citations after filtering against 0.3 and 0.7 |
| Citation limit | Set by tokens, hypothetically 2000 for this exercise | Compare citation completeness against 1000 and 4000 |
| Result reranking | Enabled | When candidates are numerous, compare ranking positions before and after reranking |
| Citation content output | Passed to the answer step | Check whether each answer item corresponds to the cited source text |
The associated knowledge bases must be checked first. Only knowledge bases with the same vector model can be associated together. When identifiers differ, exclude the non-matching one and record the observation. Do not run a cross-model retrieval to compare missed recall, and do not assert runtime outcomes such as missed recall, redundant returns or unpredictable behavior after association.
The citation limit uses tokens as the documented unit. The starting value of 2000 tokens is a hypothetical exercise value, not an official default. The reason for choosing it is to compare citation completeness against 1000 and 4000 under the same sample.
Three common errors
- Reading the credit approval status "pending review" as approved. Input: the system status field. Comparison: the two mutually exclusive values "pending review" and "approved." Observable result: whether the draft sentence matches the status field value. In this sample, the draft sentence is not supported.
- Treating the Chinese and English clauses as the same version and citing them interchangeably. Input: the two handbook source texts. Comparison: "deposit payable within 7 days" (English rendering) against "within 7 days." Observable result: whether the citation marks the specific version. If the version identifier is missing from the citation, record the gap.
- Treating retrieval output as authorized execution. Input: the search node citation array. Comparison: the citation content against the credit approval record. Observable result: whether an order action appears without a completed approval. A pending request is not an approval, and an offered option is not execution.
How to verify the setup
- Input the draft sentence "Dealer A's credit has been approved." Compare it against the system credit status field "pending review." If the two values are mutually exclusive for the same subject and the same field, the draft sentence is not supported. Expected observation: the draft sentence is judged unsupported, and the status field is recorded as pending.
- Input the Chinese Section 3 source text. Compare whether the citation output contains that paragraph and a version identifier. If the citation lacks version information, record the gap. Expected observation: the citation either carries the version identifier or the missing version is logged as an evidence gap.
- Input an empty citation array
[]. Compare whether the downstream answer step still runs through. If the downstream step treats the empty array as an error and terminates, record that as an item to verify. Expected observation: the empty array is a valid output length, and the downstream design is checked against it. This is a paper check of the downstream design, not a claim that a fictional rule returns an empty array.
These checks use the sample source text, the draft sentence and the request given above. They state expected observations. They do not claim that any test, deployment, approval, refund or other business action actually happened. Fields not provided remain unknown.