What the documents look like
Dealer ordering events serve offline dealer reservations and do not directly manage platform storefronts. The working materials come from the ordering event system, historical sales, dealer inventory and financial credit approval, with updates on a quarterly or annual rhythm. The documents handled day to day include ordering handbooks, ordering contracts, sample lists and credit approvals. When drafting product and marketing copy, a proposed sentence needs to stay consistent with the policy wording in the ordering handbook, the specification descriptions in the sample list, and the effective scope recorded in the contract and credit approval.
At the retrieval step these materials vary widely in length. Item numbers, model designations and proper nouns sit alongside natural-language policy sentences. This mix determines that the search mode and the reference limit need to be checked separately for each type of material rather than fixed once. The knowledge base search node can associate one or more knowledge bases that use the same vector model. Knowledge bases built on different vector models cannot be associated together; the correct action is to check the model identifier, exclude the ones that do not match, and record what was actually observed. Similarity and relevance scores do not carry permission or entity isolation. Retrieval is not authorization.
Constraints at the retrieval step
The reference content is output as an array, and its length can be zero. Even when nothing is found, the output path still completes. The reference limit is measured in tokens. The minimum relevance value takes effect only during semantic retrieval or when result reranking is used; it is a filter threshold, not a final ranking rule. After question optimization, hybrid retrieval, image retrieval or result reranking is enabled, the final result may pass through multi-path recall fusion and does not necessarily follow a single vector similarity order. RRF is the fusion process for combining multiple retrieval channels; it is not a switch that can be turned on. Image retrieval requires a corresponding image input and model capability, and reranking requires a rerank model that is enabled according to configuration. The optional paths shown in the overall flow diagram do not mean every request executes all of them.
A hypothetical paper exercise sample, used only for desk checking and not indicating that any real customer, approval or reservation took place: a brand channel department plans to write one ordering event product sentence. The source material available for checking consists of three sentences. "The current-season ordering handbook states that the reservation deadline for the A-type sample is 20 March." "The sample list states that the A-type sample material is aluminum alloy and the color is matte gray." "The credit approval record states that a certain dealer's credit line is in a pending-review status." The proposed sentence to be judged is: "The A-type sample uses matte gray aluminum alloy material, the dealer has completed credit approval, and reservations may continue until 25 March."
Configuration and implementation checks
| Configuration or check item | Setting in this page's sample | Basis and comparison method |
|---|---|---|
| Associated knowledge bases | Associate only the knowledge bases carrying the ordering handbook, sample list and credit approval whose vector model identifier matches | Check the vector model identifier first, exclude non-matching ones, and do not run cross-model retrieval |
| Search mode | The hypothetical trial starting point for this sample is hybrid retrieval, to cover both natural-language policy sentences and model-type terms | Try semantic retrieval and full-text retrieval separately with the sample question, and compare whether the candidate content covers the three source sentences |
| Reference limit | The hypothetical trial starting point for this sample is the token amount needed to cover the three source sentences, because all three need to enter the checking scope | Compare with a smaller limit and observe whether a source sentence is truncated; this value is not an official default |
| Minimum relevance | The hypothetical trial starting point for this sample is a 0-1 value, effective only during semantic retrieval or result reranking | Mark relevant and irrelevant content in the sample first, then compare whether the three source sentences are retained after filtering |
| Question optimization | Enabled in this hypothetical trial, for coreference resolution and question expansion | Compare the original question with the optimized question and check whether the subject has been changed incorrectly |
| Result reranking | Enabled according to configuration in this hypothetical trial, requiring a rerank model | Compare candidate order before and after reranking and observe whether the three source sentences remain checkable |
Three common errors
- Treating pending review as approved. The source text states the credit line is in a pending-review status, while the proposed sentence writes that the dealer has completed credit approval. This is the same field with its value rewritten. The check is to compare the original value of that field in the credit approval record against the proposed sentence.
- Rewriting the deadline to a later date. The source text states the deadline is 20 March, while the proposed sentence writes that reservations may continue until 25 March. This is the same field with inconsistent values. The check is to compare the date field in the ordering handbook against the date in the proposed sentence.
- Treating an unstated material or color as confirmed. If the proposed sentence contains a material or color not stated in the sample list, it is unsupported. The check is to compare each sample list field against the proposed sentence item by item and record a gap where a field is missing.
How to verify the setup
- Input the three source sentences and the proposed sentence, then compare "has completed credit approval" in the proposed sentence against "pending review" in the credit approval record for the same subject, the same period and the same field. The support condition is met only when that field's source text explicitly reads as approved. In this sample it reads as pending review, so the judgment is unsupported.
- Input the three source sentences and the proposed sentence, then compare "reservations may continue until 25 March" in the proposed sentence against the deadline field in the ordering handbook. The support condition is met only when that field's source text explicitly reads as 25 March or later. In this sample it reads as 20 March, so the judgment is inconsistent.
- Input the three source sentences and the proposed sentence, then compare whether the material and color in the proposed sentence can be found with corresponding values in the same sample list fields. The support condition is met only when the sample list explicitly states that material and color. In this sample the material and color are stated as aluminum alloy and matte gray, so those two items are supported, while the credit and date items are not. The overall judgment is partially unsupported, and the gaps remain pending verification.