What the documents look like
Refund-only dispute handling under the inventory procurement and supplier materials task works mainly from platform after-sales backend records: refund-only applications, shipment evidence, proof of receipt, and appeal materials. Compared with ordinary return-and-refund cases, refund-only disputes frequently have no returned goods entering the warehouse, so the evidential focus falls on dispatch, signed receipt, and the value of the goods. Document parsing therefore has to cover the application form, carrier tracking screenshots, outbound warehouse records, and supplier correspondence together. These materials update per order and daily, and the parsing result directly affects whether an appeal can quickly locate the dispatch and receipt evidence for the matching order.
Constraints at the document chunking step
Chunking needs to preserve a document identity and version that can be traced back to the source text. A single refund-only application may contain the stated reason, the amount, the order number, and communication records. If a condition, an explanation, and the content it governs are split apart, retrieval tends to return incomplete fragments. On storage, source data and retrieval indexes need to be distinguished: one group of source data can correspond to multiple indexes, and the vector score takes the highest score. Retrieval first recalls vectors, then uses the vector ID to find the source data in MongoDB; records corresponding to the same group of source data are merged.
Hypothetical drill sample: the source text available for comparison reads, "Order A's refund-only application was submitted on 10 March, stating that the outer packaging of the goods was damaged, with a requested amount of 120 yuan. The warehouse outbound record shows the order was dispatched on 8 March, and the carrier tracking shows it was signed for on 9 March." The draft sentence to be assessed is, "The order has completed signed receipt; approve the refund-only application." In this sample the material supports only the fact of signed receipt. It contains no authorization record for approving a refund, so the approval conclusion in the draft sentence lacks support.
Configuration and implementation checks
| Check item | Hypothetical trial starting value | Reason and comparison method |
|---|---|---|
| Segmentation approach | Separate segments for the application form, outbound record, and tracking screenshot | Compare with merging the whole order into one segment; observe whether receipt evidence can be hit on its own during retrieval |
| Reference limit | Set to 2000 tokens | Compare with 1000 tokens; observe whether the receipt and the application reason are both cited |
| Minimum relevance | Set to 0.4 | Compare with 0.2; observe whether irrelevant fragments decrease |
| Search mode | Hybrid search | Compare with semantic search alone; observe hits for order-number queries |
| Question optimization | Left off for now | Compare with it enabled; observe whether a single clear question is affected |
| Rerank | Not enabled for now | Compare with it enabled; observe ordering changes when candidates are numerous |
The values above are hypothetical trial starting points for comparison against another set of values. They are not official defaults.
Three common errors
- Treating a successful upload as retrieval already updated. Uploading, training, and index status are separate stages. After material changes, the actual training and index status need to be checked; the retrieval result cannot be assumed to reflect the new content.
- Treating a retrieval result as the basis for authorization. Retrieval, or a value collected in a form, does not constitute approval of a refund, a passed review, or business execution. The approval conclusion in the draft sentence requires a separate authorization record.
- Treating minimum relevance as a permission or entity filter. A relevance score does not exclude unrelated business or unauthorized records, and retrieval itself does not perform authorization judgment.
How to verify the setup
- Input the source text and the draft sentence from the hypothetical sample above, and compare whether the approval conclusion in the draft sentence has material support. If the material contains only the fact of signed receipt, the approval conclusion is unsupported and the evidence gap must be recorded.
- Input the order number "Order A" for retrieval, and compare whether the returned content includes both the application reason and the receipt record for that order. If only the application reason returns without the receipt record, segmentation or the reference limit needs review.
- Input a clearly paper-based empty result [] to check the downstream design, and observe how the system handles the empty-reference path. No claim can be made that a fictional rule retrieval necessarily returns []; the output actually observed must be recorded.