What the documents look like
For product questions in Refund-only disputes, this page examines FastGPT document chunking. A request description and a product-specification source must retain their different identities. The examples are hypothetical.
Constraints at the document chunking step
A proposed refund-related product exercise includes a request excerpt saying the buyer describes a loose lid and a specification page describing a screw-fit closure. No inspection of that item is supplied. A question about a general loose-lid problem concerns a scope neither passage establishes: one is individual feedback and the other structural type. Parsing must preserve buyer-description and specification identities. Feedback cannot enter a specification block as a confirmed defect, and a screw-fit design cannot establish that every individual lid is free from problems. Screw-fit also gives no degree of tightness, so it cannot rebut this particular report. Item condition needs an applicable inspection, while a general performance conclusion needs evidence covering that wider scope; shared lid vocabulary cannot merge those separate gaps.
Configuration and implementation checks
| Original or chunk check | Specific source relationship | Evidence action |
|---|---|---|
| Feedback identity | Buyer describes | Check attribution survives trimming. |
| Specification subject | Screw-fit structure | Do not treat as item inspection. |
| Scope difference | Individual item and whole product line | Check conclusions do not expand. |
| Evidence gaps | Item inspection and product-wide basis absent | Retain separate unresolved targets. |
| Inspection update | Inspection subject and cited version | Check processing and same-question returns. |
Documented conditions
| Documented item / implementation check | Condition |
|---|---|
Original-document check | Compare original files with parsed output. |
Chunk completeness | Keep conditions traceable to their subjects. |
Data and indexes | Retain original-data and index evidence separately. |
Sample retrieval | Retest literal wording and natural questions. |
Post-update check | Inspect training or index state after updates. |
Three common errors
One failure trims buyer describes and leaves loose lid as an asserted product finding. Another parses the request and specification as one source, making a structural note appear to be an inspection of the particular item. Compare document identities, statement subjects and actual blocks to distinguish lost attribution from mixed evidence types. Retrieving loose cannot verify the claim, while retrieving screw-fit cannot rule it out. Without inspection material, the source-reading exercise should not decide the product condition or responsibility for the reported issue.
How to verify the setup
Acceptance should ask what the buyer reported, what the specification states and whether an item inspection or product-wide basis exists. Returned blocks should provide distinct coverage. Preserve feedback identity and structural wording while leaving broader conclusions unresolved. If an inspection record is added, check its applicable item, actual processing and index state before retesting; upload alone cannot establish that feedback was confirmed or disproved. Retain original and citation versions so a new inspection subject does not replace the older case identity or extend an item-specific result to all products.
| Material context | Scope |
|---|---|
| Document types | Refund-Only Application, Proof of Shipment, Proof of Receipt and Appeal Materials |
| Candidate sources | Platform After-Sales Backend, Carrier Tracking, Customer Service Chat and Warehouse Outbound Records |
| Technical baseline | FastGPT v4.17.2 |