What the documents look like
Refund-only disputes frequently proceed without any returned goods arriving at a warehouse. The evidentiary weight therefore falls on dispatch and delivery records and on the stated value of the goods. The main sources named in the brief are the platform after-sales console, carrier tracking, customer service chat logs, and warehouse outbound records. The brief gives two update frequencies, per order and daily; this page does not derive batch synchronization, full synchronization, real-time processing, or transaction-triggered processing from either of them.
Four document types carry the retrieval load for this category: refund-only applications, dispatch evidence, proof of delivery, and appeal materials. Each has a different center of gravity. A refund-only application states what the buyer wants and why. Dispatch evidence shows that goods left the seller. Proof of delivery shows what the carrier recorded at the destination. Appeal materials assemble the seller's position for the platform. Because no return parcel exists in many of these cases, the retrieval system is often asked to surface dispatch and delivery records rather than inbound inspection results, and the value question is argued from the order record and the listing rather than from a returned item.
The three most time-consuming steps named in the brief are deciding whether a return is required, collecting logistics evidence, and submitting a platform appeal. Retrieval supports all three by making the underlying documents reachable, and it does none of them on its own.
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 practical step is to check the vector model identifier and exclude bases that do not match, then record what was actually observed. This page does not extend the same-vector-model requirement to business registration sites or any other external system.
The node outputs cited content as an array, and the length may be zero. When nothing is retrieved, the output path still runs. A downstream design that assumes at least one citation will not match this documented behavior.
Minimum relevance is a filter threshold. It takes effect only under semantic retrieval or when result reranking is used. It is not a final ordering rule, and it does not perform permission or entity isolation. Retrieval and recall do not constitute authorization.
Hypothetical paper exercise sample: a paper record states "Order A was delivered by the carrier on March 1; the recipient field is blank. On March 4 the merchant submitted dispatch evidence and the outbound record; the after-sales console status is pending review." A draft sentence awaiting judgment reads: "This order is confirmed as delivered, so the refund-only rejection can be supported."
Checking that sentence: the blank recipient field is an unstated item, not a negative finding and not a conflict. Pending review does not show that operating permission is absent, and it does not equal approval. The draft sentence turns an unsupported delivery fact into a confirmed one and goes beyond the material. The evidence gap stays open.
Configuration and implementation checks
The table below concerns the sample above and lists only documented settings or implementation checks. The values are starting points for this hypothetical exercise and are not official defaults.
| Item | Hypothetical starting point for this exercise | Reason and comparison object |
|---|---|---|
| Associated knowledge bases | Associate one base that uses the same vector model | Check the vector model identifier first and compare it item by item against candidate base identifiers |
| Search mode | Run semantic retrieval and full-text retrieval separately | Compare the cited content each path returns for the same question |
| Citation limit | Set to the token volume needed to cover a complete passage of the sample material | Compare against actual materials of differing length to see whether content stays complete |
| Minimum relevance | Label relevant and irrelevant samples first, then set the threshold | Takes effect only under semantic retrieval or result reranking |
| Question optimization | Compare short questions and multi-turn follow-ups separately | Check whether the subject is altered incorrectly after optimization |
| Result reranking | Compare when a model is available and enabled per configuration | Compare candidate ordering before and after reranking |
Three common errors
- Treating retrieval or a form as authorization to act. The input is a retrieval request; the comparison object is the authorization status field; the observable result is whether the two have been conflated.
- Treating an unstated field as a denial or a conflict. The input is the blank recipient field; the comparison object is the phrase "confirmed as delivered"; the observable result is that the phrase is unsupported by the material.
- Treating pending review as approval or rejection. The input is the pending review status in the after-sales console; the comparison object is the conclusion in the draft sentence; the observable result is that the conclusion exceeds the material.
How to verify the setup
- Input the sample material text and the draft sentence. Compare whether the draft sentence introduces a delivery fact not stated in the source. The expected observation is that the sentence is unsupported; this page does not claim the check has been run.
- Input the same question through semantic retrieval and through full-text retrieval. Compare the cited content from each path against the sample material. The expected observation is whether any passage unrelated to the question subject is cited.
- Input an explicit paper empty result, written as []. Compare whether the downstream design handles it as an empty array. The expected observation is whether any unsupported automatic business action appears. A pending request is not approval, and an offered option is not execution.