What the documents look like
Brand dealer ordering events run on a quarterly or annual cycle. A brand channel department collects reservation quantities from offline dealers. The working materials for a comparison task include the ordering handbook, the ordering contract, the sample list, and the credit approval. Each carries a different role: the handbook states policy and product scope, the contract records what the two sides agreed, the sample list names physical objects, and the credit approval reflects the status of a credit line. These materials update infrequently, and the same batch is cited repeatedly before and after the event. Retrieval therefore has to distinguish different versions of the same dealer across different event periods.
The category differs from platform multi-store matrix management: an ordering event serves offline dealer reservations and does not directly manage platform storefronts. The consequence of error is under-ordering, inventory pressure disputes, or collection risk. The most time-consuming steps are explaining new product policy, collecting order quantities, and approving credit lines.
Constraints at the retrieval step
The knowledge base search node can associate one or more knowledge bases that use the same vector model. Knowledge bases with different vector models cannot be associated together; the identifiers must be checked first and non-matching bases excluded. Search mode is compared across semantic search, full-text search, and hybrid search according to the test question, and no single mode is assumed to suit all materials. The citation limit is measured in tokens. The minimum relevance value takes effect only under semantic search or when result reranking is used. Question optimization performs coreference resolution and question expansion. A similarity score is a relevance measure and does not perform permission or entity isolation; retrieval itself does not constitute authorization.
Hypothetical paper exercise sample: a brand channel department intends to check one material. The material text reads: "East China dealer A, 2024 autumn ordering event, ordering contract number QD-2024A-017, agreed category is outdoor footwear, signing status is signed, effective status is pending confirmation by the brand's legal department." The draft sentence to be judged is: "Dealer A's 2024 autumn ordering contract has taken effect." The source text only gives a record whose effective matter is pending legal confirmation; it does not state a conclusion that confirmation was given or that the contract is not effective. The phrase "has taken effect" in the draft sentence lacks supporting evidence and remains to be verified.
Configuration and implementation checks
| Configuration item | Setting on this page | Explanation |
|---|---|---|
| Associated knowledge bases | Ordering handbook base, ordering contract base, sample list base, credit approval base | The four bases use the same vector model, so they can be associated together |
| Search mode | Hypothetical starting point for this exercise is hybrid search | Contract number questions need full-text hits, policy descriptions need semantic hits, so hybrid is tried first |
| Citation limit | Hypothetical starting point for this exercise is 3000 tokens | Ordering contract passages vary greatly in length; this value makes it easier to compare complete passages against truncated ones |
| Minimum relevance | Hypothetical starting point for this exercise is 0.3 | Relevant and irrelevant samples are labelled first, then compared with 0.2 and 0.4 |
| Question optimization | Hypothetical starting point for this exercise is enabled | Follow-up questions contain references; the original question and the optimized question are compared to see whether the subject was altered |
| Result reranking | Hypothetical starting point for this exercise is enabled | When candidates are numerous, text is re-sorted, and the rerank score can be used for filtering |
These starting values are exercise assumptions, not official defaults. Each needs a stated reason and a comparison method before any change is considered.
Three common errors
- Treating a retrieval hit as authorization to execute. Retrieving an ordering contract or credit approval record only shows that the content exists in the base; it does not show that approval passed, that the contract took effect, or that collection completed. Check: input the same contract number, compare the retrieval result with the approval status field, and observe whether the result only returns text without triggering any business action.
- Treating a similarity score as permission or entity filtering. The minimum relevance value only filters low-relevance results; it does not exclude unrelated dealers or unauthorized records. Check: input a question about dealer A, compare whether materials for dealer B appear in the returned content, and observe whether score level and subject ownership agree.
- Treating a pending review as a negation or a conflict. When the material only says "pending confirmation by the brand's legal department," this is unsupported; it does not constitute a denial that the contract is effective. Check: input the draft sentence and the source text, compare the value of the same field, and observe whether a clearly mutually exclusive value exists.
How to verify the setup
- Input the material text and the draft sentence "Dealer A's 2024 autumn ordering contract has taken effect." Compare the two values "pending confirmation by the brand's legal department" and "has taken effect." If the system does not judge the draft sentence as supported and preserves the evidence gap, the behaviour matches expectation.
- Input contract number QD-2024A-017 and compare what full-text search and semantic search return. If a number-type question can hit the passage containing that number under full-text or hybrid mode, the behaviour matches expectation; when no hit occurs, record it as an observation.
- Input the paper empty result [] and compare how the downstream node handles that array. If the citation content has length 0 and the chain still runs through, the behaviour matches expectation; whether an actual retrieval returns an empty array still needs to be recorded as an observation.