What the documents look like
Retail plastic bag and single-use item reporting sits on a different business line from cashier membership and promotion work. It revolves around disposable plastic product reporting and environmental supervision. The materials handled day to day include plastic bag procurement ledgers, sales vouchers, semiannual reports, and self-discipline commitments. Data arrives from the Ministry of Commerce reporting system, POS plastic bag sales, the procurement system, and store ledgers, with update frequencies of semiannual and daily. Order fulfillment and after-sales question handling in this category must answer customer or internal questions about the basis of a report, the ledger record, and the commitment document. These materials take the form of ledger entries, voucher images, report text, and scanned commitment letters. The retrieval step needs to anchor an answer to the original text position in a specific material.
Constraints at the citation tracing step
The knowledge base search node selects one or more knowledge bases that share the same vector model as the retrieval scope. Its output is an array of citations, and the length may be zero, which means the output path still runs even when no content is found. Citation content is passed to the answering step, where each answer statement is checked against the cited original text. The minimum relevance value is a filter threshold and takes effect only under semantic retrieval or result reranking; it does not perform permission or entity isolation. Hybrid retrieval merges multiple result paths through RRF, and reranking requires a model and runs according to the setting. Image retrieval requires image input and model capability, and does not execute on every request. Knowledge bases with different vector models cannot be associated together; the identifiers should be checked first and non-matching bases excluded.
Hypothetical drill sample: a retail store submits an excerpt from a plastic bag procurement ledger, with the original text "From March 1, 2025 to June 30, 2025, this store procured a total of 12,000 disposable plastic bags, supplier was a packaging factory, corresponding purchase order number CG-2025-0312." A separate sales voucher excerpt reads "From March 1, 2025 to June 30, 2025, this store's POS system recorded plastic bag sales revenue of 3,600 yuan." A draft sentence to be assessed reads "In the first half of 2025, this store's plastic bag procurement volume and sales volume were consistent, and all were sold." This draft sentence must be compared against the two original texts to determine whether procurement quantity and sales quantity form mutually exclusive values under the same period and the same field, or remain unsupported.
Configuration and implementation checks
| Configuration item | Assumed trial starting point for this page | Reason for the choice and comparison method |
|---|---|---|
| Associated knowledge bases | Select knowledge bases that already contain plastic bag procurement ledgers, sales vouchers, semiannual reports, and self-discipline commitments | Check the vector model identifier of each base; only bases with the same vector model may be associated together, and non-matching bases are excluded |
| Search mode | Hybrid retrieval | Ledgers contain exact fields such as order numbers and amounts; hybrid retrieval uses semantic recall and full-text recall together and merges them through RRF |
| Citation limit | The operator fills in a tokens value according to the needs of this check | This value is a starting point for this hypothetical trial, compared against the original text length needed for the answer; no fixed default is assumed |
| Minimum relevance | The operator fills in a value from 0 to 1 according to the needs of this check | This value takes effect only under semantic retrieval or result reranking, is compared against candidate result scores, and does not act as a permission filter |
| Result reranking | Enabled according to the setting when a rerank model is configured | Reranking produces a score from 0 to 1, compared against the minimum relevance value; it is not enabled when no rerank model is configured |
| Citation output handoff | Pass the citation array to the answering step | Check whether each answer statement corresponds item by item to the cited original text, and inspect the downstream design when the array is empty |
Three common errors
- Treating a retrieval hit as an authorized action. A retrieval returning a citation array only shows that content was found; it does not mean the order was fulfilled, the after-sales request was approved, or the ledger was written. The input is the retrieval result, the comparison is against the business authorization status field, and the observable result is that the authorization status remains pending review or is not stated.
- Associating knowledge bases with different vector models together. The input is the vector model identifier of each base, the comparison is whether the identifiers match, and the observable result is that non-matching bases are excluded, without running a cross-model retrieval to compare missed recall.
- Judging the procurement quantity and sales quantity in the draft sentence as directly consistent. The input is the ledger original text and the voucher original text, the comparison is the values under the same period and the same field, and the observable result is that procurement quantity and sales quantity do not form mutually exclusive values under the same field, so the draft sentence remains unsupported.
How to verify the setup
- Use the ledger original text and voucher original text from the hypothetical drill sample as the retrieval input, compare whether the citation content returned by retrieval contains these two original passages, and observe whether the corresponding original text appears item by item in the citation array and whether the citation position in the answering step matches the original text.
- Use the draft sentence "In the first half of 2025, this store's plastic bag procurement volume and sales volume were consistent, and all were sold" as the input to be assessed, compare the period and field of the draft sentence against the two original texts, and observe whether procurement quantity and sales quantity fail to form mutually exclusive values under the same field, so the sentence is judged unsupported.
- Use a clearly labeled paper input of an empty array to check the downstream design, compare the output after the empty array enters the answering step, and observe whether the output path runs through without error, without claiming that a fictional rule retrieval necessarily returns an empty array.