What the documents look like
Category qualification access happens before listing or onboarding, and the core materials are the business license, trademark registration certificate, brand authorization chain, and industry license. Channel operations staff, onboarding specialists, and brand-side channel managers work with these materials to prepare product information and answer selection questions. Material updates are irregular; each onboarding round requires re-checking the current version. Citation tracing addresses one question: whether a qualification statement in an answer can be mapped to specific source text, and what state that source material is in.
Three industry facts shape this task. First, the access decision occurs before listing, so the evidence base is pre-approval material rather than post-sale records. Second, the authorization chain is the most time-consuming item to collect, which means answers frequently rest on partial chains. Third, the materials come from several registries with different update rhythms, so a retrieved document may be a superseded version. These facts affect citation tracing because a fluent answer is not evidence that the cited material is current, complete, or within the stated authorization boundary.
Constraints at the citation tracing step
The knowledge base search node selects one or more knowledge bases that share the same vector model, and outputs citations as an array whose length may be zero. A zero-length array still lets the downstream chain run. The answer step receives that array and compares each item against source text. Retrieval does not constitute authorization and does not decide whether a material is valid.
The minimum relevance setting takes effect only in semantic retrieval or when result reranking is used. It filters low-relevance results; it does not perform subject isolation or permission filtering. Hybrid retrieval merges multiple result paths through RRF. Reranking requires a model and must be enabled by configuration. Image retrieval requires image input and model capability. These optional paths do not run on every request merely because a flow diagram lists them. Knowledge bases with different vector models cannot be associated together; check the model identifier first and exclude non-matching bases rather than running a cross-model search to compare recall.
Hypothetical paper exercise sample: an onboarding specialist submits a brand authorization chain material. The source text reads: "Authorizing party A, authorized party B, authorized brand C, authorization period from January 1, 2026 to December 31, 2026, scope of authorization online sales." A proposed sentence reads: "B has obtained long-term authorization for brand C." The question is whether the proposed sentence matches the source text.
Configuration and implementation checks
| Configuration item | Hypothetical starting point for this exercise | Reason and comparison method |
|---|---|---|
| Associated knowledge bases | Select one qualification material base | Check the vector model identifier of each base; only matching identifiers may be associated together |
| Search mode | Hybrid retrieval | Compare against semantic retrieval for hits on certificate numbers and license names |
| Minimum relevance | Starting point 0.5 for this exercise | Compare with 0.3 and 0.7, observing whether unrelated fragments decrease |
| Citation limit | Starting point 2000 tokens for this exercise | Compare with 1000 and 4000, observing whether citations are truncated |
| Question optimization | Off | Compare with on, observing retrieval effect and latency for short questions |
| Result reranking | Off | Compare with on, observing whether ordering improves when candidates are numerous |
The values above are starting points for this paper exercise, not official defaults. The citation limit uses the documented token unit. The thinking budget documented for AI configuration is a reasoning budget and is not the citation token limit.
Three common errors
- Rewriting the authorization period "January 1, 2026 to December 31, 2026" as "long-term authorization." Input: the source text and the proposed sentence. Compare the period field. The proposed sentence exceeds the validity range stated in the source, so it is unsupported.
- Treating a retrieval hit as an authorization already in effect. Input: the citation array and the material state. Compare whether signing or effective-date information is stated. When the source does not state it, record the item as pending verification.
- Treating an empty citation array as a workflow error. Input: the paper array []. Compare the downstream answer design. A zero-length array still lets the chain run, and no business rejection action is produced.
How to verify the setup
- Input the hypothetical source text and the proposed sentence "B has obtained long-term authorization for brand C." Compare the authorization period field. The source states only the single year 2026, so the proposed sentence does not match the source and should be rewritten to match the source wording.
- Input the hypothetical source text and the proposed sentence "B obtained online sales authorization for brand C in 2026." Compare the four fields of party, object, period, and scope. All four can be mapped to the source, so the consistency condition is met.
- Input the paper array [] and the downstream answer design. Compare whether the chain continues when the array is empty, and observe whether an answer can still be generated. Do not judge this as a retrieval failure.
For the first check, the expected observation is a mismatch on the period field, and the failure branch is a proposed sentence that extends beyond the stated range. For the second, the expected observation is that all four fields correspond, and the failure branch is any field that cannot be mapped. For the third, the expected observation is that the downstream step still runs; whether an answer is produced depends on the downstream design and remains to be observed, not asserted.