What the documents look like
Returns refurbishment and resale handle reverse logistics and item condition. This differs from first-leg replenishment management, which covers inbound stock movement. The main data sources are the overseas warehouse WMS, the TikTok return center, Amazon return reports, and product quality inspection photos. Daily documents include return quality inspection forms, refurbishment records, scrap sheets, and resale listing lists. Updates occur daily or per batch.
These materials determine which item states, inspection conclusions, and listing scopes a draft copy sentence may cite. A draft sentence about a returned item rests on the inspection form and the refurbishment record, not on the warehouse stock figure alone. When a refurbishment record states that a function works after a housing replacement, that statement supports a functional claim. It does not by itself support a saleability claim, because the record does not carry that conclusion.
Constraints at the citation tracing step
Knowledge base search first confirms the selected knowledge bases and the document version. Only knowledge bases that share the same vector model can be associated together. The search node outputs a citation array, and its length may be zero. An empty array does not mean the workflow has errored or stopped. The retrieval output passes to the answering step, where each answer sentence is checked against the cited source text. A traceable sample is used to check the displayed source text. A thinking process or a fluent answer does not replace source evidence. Current-version and historical-version documents are used to test the source, and whether a citation is adopted still depends on valid-version review. The minimum relevance value filters low-relevance results only. It does not perform permission or entity isolation. Retrieval is not authorization.
Hypothetical drill sample: the source text reads, "March 2025 batch A-17 refurbishment record: the subject is the overseas warehouse quality inspection team, the object is a returned earphone, the state is that function is normal after housing replacement, and the valid scope is item 3 of the resale listing list." The draft sentence to be judged reads, "This batch of earphones works normally after refurbishment and can be resold." The source text records only that function is normal and that the item is listed. It does not record a saleability conclusion. The draft sentence is unsupported.
Configuration and implementation checks
| Configuration item | Hypothetical starting point for this drill | Comparison and explanation |
|---|---|---|
| Associated knowledge bases | Select knowledge bases sharing the vector model of the inspection materials | Check the identifier first and exclude those with a different vector model |
| Search mode | Hybrid search | Compare recall differences against semantic search results |
| Minimum relevance | Hypothetical starting value 0.5 | Compare filtered counts against 0.3 and 0.7 |
| Citation limit | Hypothetical starting value 2000 tokens | Compare citation completeness against 1000 and 4000 |
| Result rerank | Enable after configuring a ReRank model | Compare ordering before and after rerank |
| Reply format | Keep the default | Change only when a later step must read a fixed format |
These values are hypothetical starting points for this drill, chosen to give a middle setting for comparison. They are not official defaults.
Three common errors
- Writing "works normally after refurbishment" directly as "can be resold." The check input is the source text and the draft sentence. The comparison is whether the draft sentence contains a sales conclusion absent from the source text. A draft sentence containing an unsupported conclusion fails the check.
- Treating the minimum relevance value as a permission filter. The check input is the relevance setting and an out-of-scope query. The comparison is whether returned records exceed the authorized range. Returned out-of-scope records fail the check.
- Treating an empty citation array as a workflow error. The check input is a paper output of []. The comparison is whether the downstream node continues to execute. A downstream halt fails the check.
How to verify the setup
- Input the hypothetical drill source text and the draft sentence. Compare whether the draft sentence is supported by the source text. The condition is met when the draft sentence is marked unsupported.
- Input knowledge base identifiers for the same vector model and for a different vector model. Compare whether only the same-vector-model knowledge bases are associated. The condition is met when the different-vector-model knowledge base is excluded.
- Input a paper citation array of []. Compare whether the downstream answering step runs through. The condition is met when the downstream does not halt because of the empty array.
These are paper checks. No test has been executed, and no deployment, approval, or business action has taken place.