What the documents look like
Amazon FBM fulfillment is handled by the seller, who also configures the return address, and it does not rely on platform warehouse inspection. The daily document line for this category consists of order picking lists, shipment confirmation records, return address settings, and logistics tracking sheets. Data sources include Amazon Seller Central, carrier systems, ERP orders, and customer service email, with updates occurring per order or per day. In cross-border material and multilingual retrieval, the same batch of material often exists in Chinese and English or several languages in parallel. A retrieval result needs to point back to specific document text so that later handover and cross-checking can proceed. The core of citation tracing is that every cited item can be located to a material, a version, and a validity scope. The retrieval output itself does not constitute any authorization.
Three facts from this category shape the citation tracing step. First, because the seller handles fulfillment and return address configuration, the materials that must be traceable include the return address setting page, not only the shipment record. Second, the data sources are split across Seller Central, carrier systems, ERP orders, and email, so a single retrieval result may need to be traced to more than one origin. Third, updates happen per order or per day, so a citation that was accurate for one version of a material may not match the current version.
Constraints at the citation tracing step
The knowledge base search node can associate one or more knowledge bases that share the same vector model. Its citation output is an array, and the length may be zero. A zero-length array means the output path still runs even when no content is retrieved. An empty array is not a workflow error termination.
A similarity score is a relevance number. It does not perform permission, entity, or business scope filtering. Retrieving a piece of content does not mean the order, return, or shipment operation described by that content has been authorized.
Hybrid retrieval merges multiple result paths through RRF. RRF is a fusion process, not a switch that can be turned on. Reranking requires a ReRank model and must be enabled according to settings. Image retrieval requires image input and model capability. These optional paths are not all executed on every request.
The citation limit controls the amount of cited content in tokens, and it is unrelated to thinking budget. Knowledge bases with different vector models cannot be associated together. The identifier must be checked first and non-matching bases excluded; cross-model retrieval is not executed to compare missed recalls.
Configuration and implementation checks
Hypothetical paper exercise sample: an FBM seller's customer service role receives a draft sentence awaiting determination — "Order A-1024 has completed return receipt per return address R-07, refund executed the same day." The material text available for comparison consists of three sentences. First: "The shipment confirmation record for order A-1024 states carrier C-3, tracking number T-88, shipment date June 3, 2024." Second: "The return address settings page shows R-07, effective date May 20, 2024, applicable store S-1." Third: "Customer service email record: the customer asked about return progress on June 10, 2024, and attached no receipt proof." The material does not state the receipt fact or the refund execution. The configuration below centers on citation tracing for this sample.
| Configuration item | Hypothetical trial starting point for this exercise | Reason for the choice and comparison method |
|---|---|---|
| Associated knowledge bases | Associate only the S-1 store material base | First check whether the vector model identifiers of each base are the same; exclude those that differ; do not execute cross-model retrieval |
| Search mode | Hybrid retrieval | The draft contains order number A-1024 and natural language description, so both number matching and semantic recall need coverage |
| Citation limit | Set to 800 tokens | The three sample sentences are short; compare with the citation volume when no limit is set, and observe whether all three sentences are covered |
| Minimum relevance | Set to 0.5 | Compare with 0.3 and 0.7, observe whether the three sentences still enter the citation array, and record the actual observation |
| Result reranking | Enabled | A ReRank model is required; compare candidate ordering with the disabled state; this is not a permission filter |
| Citation content output | Check the citation array length | Use the explicit paper input [] to check the downstream design; do not claim that a fictional rule retrieval will certainly return [] |
Three common errors
- Treating the draft sentence's claim "has completed return receipt per return address R-07, refund executed the same day" as a verified fact. The material text states only the effective scope of return address R-07 and the shipment information; it does not state receipt or refund. Input: the three material sentences and the draft sentence. Comparison object: the receipt and refund facts asserted by the draft sentence. Observable result: no corresponding field exists in the material, so the claim is recorded as unsupported and pending verification.
- Treating the similarity score or minimum relevance as a permission or entity filter, and assuming the retrieval result has excluded unrelated stores or unauthorized records. Input: a retrieval request against the S-1 store material base. Comparison object: the score and the authorization status, which are two different fields. Observable result: the score does not change authorization, so retrieval does not carry an authorization function.
- Mixing the token value of the citation limit with thinking budget, or describing RRF as a switch that can be turned on. Input: the search parameter settings. Comparison object: the citation limit unit and the thinking budget field. Observable result: the two belong to different configurations and must not be substituted for each other.
How to verify the setup
- Use the three material sentences as retrieval input. Compare whether each item in the citation array can be located to the shipment confirmation record, the return address settings page, and the customer service email record. Observe whether each citation carries a traceable original text fragment. If the citation array is empty, record the gap and do not judge it as an error.
- Use the draft sentence "Order A-1024 has completed return receipt per return address R-07, refund executed the same day" as the object to be determined. Compare the assertions in the draft sentence with the fields in the material text. Observe whether receipt and refund are stated in the material. When they are not stated, record the claim as unsupported and do not supply authorization or effective clauses.
- Use the explicit paper input [] to check the downstream receiving design. Compare whether an empty array still passes through the output path. Observe whether the downstream distinguishes an empty citation from an error. Do not claim that a fictional rule retrieval will certainly return []; record only the observation from this exercise.