What the documents look like
Retail checkout and loyalty materials center on price and member benefits rather than short-shelf-life stock. The primary sources are the POS system, member CRM, payment platforms and the price-tag system. The documents handled day to day are promotional price tags, member points rules, checkout daily reports and exception refund slips. For procurement and supplier records, the same category appears as purchase prices for promoted goods, supplier settlement statements and return or exchange vouchers. Errors surface as price complaints, cash shortfalls or overages, and member benefit disputes. Retrieval therefore has to make price, points and refund materials individually findable while preserving each item's effective range and authorization state. Update frequency is daily or per shift; that cadence does not by itself define any retrieval feature on this page.
Constraints at the retrieval step
The knowledge base search node can associate one or more knowledge bases that use the same vector model. Bases built on different vector models cannot be associated together; the operator verifies the vector model identifier first, excludes any that do not match, and records what was actually observed. A cross-model search is not executed to compare missed recalls.
Search mode is compared per test question across semantic, full-text and hybrid retrieval; no single mode is presumed suitable for every material. The citation cap is measured in tokens, so actual documents of differing lengths are used to test whether content stays complete before the cap is adjusted. Minimum relevance takes effect only under semantic retrieval or when result reranking is used, so relevant and irrelevant samples are labeled before the threshold is tuned. Question optimization performs coreference resolution and question expansion; the original question and the optimized question are compared to check whether the subject was altered. Retrieval output is an array of citations whose length can be zero, and the output path still completes when nothing is found. Retrieval obtains citation content; it does not perform authorization decisions. Pending review, quoted, signed and effective are distinct states, and retrieving a document does not mean the corresponding business action has been carried out.
Configuration and implementation checks
Hypothetical paper exercise: purchase-price reconciliation for a store's promoted product, "Brand A 500 ml beverage," covering 1 June 2025 to 30 June 2025. Source text one: "The promotional purchase price for Brand A 500 ml beverage at this store from 1 June 2025 to 30 June 2025 is 48 yuan per case." Source text two: "Supplier settlement statement number J-2025-0612 records 120 cases of the above product supplied in June at a unit price of 48 yuan, with settlement status pending review." Proposed handover request for judgment: "Please confirm that this supplier's June payment has been settled and that supply may continue." The phrase "has been settled" in that request is an unsupported conclusion; source text two shows only pending review.
| Configuration item | Hypothetical trial starting point and reason | Comparison method |
|---|---|---|
| Associated knowledge bases | Select the promotional price-tag base and the settlement-statement base, which share the same vector model identifier | Verify the identifiers match before associating together; exclude any base whose identifier differs |
| Search mode | Test natural-language phrasing with semantic retrieval first, then test the settlement statement number with full-text retrieval | Run the same question under each mode and compare the recalled content |
| Citation cap | Start at a length covering one complete settlement statement, because the sample contains a number and a status field | Compare against a shorter cap and observe whether fields are truncated |
| Minimum relevance | Label source text one and source text two as relevant and an unrelated price tag as irrelevant | Adjust the threshold and observe whether the unrelated price tag is still cited |
| Question optimization | Enable it for follow-up questions containing references; disable it for a complete identifier query | Compare the original and optimized questions and check whether the subject was altered |
Three common errors
- Reading "pending review" in source text two as "has been settled." The input is the settlement statement text, the comparison is the value of the settlement status field, and the observed result is pending review, so the request is unsupported.
- Treating retrieval of source text one as grounds to authorize continued supply. The input is the promotional purchase-price text, the comparison is whether its content contains an authorization clause, and the observed result is that it states only price and period, so the authorization fact is missing.
- Forcing knowledge bases with different vector models into a shared association. The input is the vector model identifiers of the two bases, the comparison is whether the identifiers match, and the observed result is exclusion when they differ, with no cross-model search performed.
How to verify the setup
- Input source text two and the proposed handover request; compare the settlement status field value against "has been settled" in the request. The observed result is pending review, the judgment is unsupported, and the evidence gap is recorded.
- Input source text one and the follow-up question "What is the June purchase price for this product?"; compare whether the optimized question retains the product, the period and the field. The check passes when the observed result shows the subject was not altered.
- Input an explicit paper empty result []; compare whether the downstream design accepts the empty-citation path. The check passes when the observed result shows the path completes and no fabricated content is produced. All of the above are paper checks and no live test is claimed.