What the documents look like
Tmall flagship store operations sit inside a context of brand authorization, flagship store identity, and Tmall points compensation rules. The cross-border materials and multilingual retrieval task handles four document types: product listing pages, brand authorization letters, delivery commitment records, and after-sales tickets. Data sources are the Tmall merchant backend, the Tmall rules center, ERP order tables, and customer service chat records. Updates arrive daily and per order.
These features shape citation tracing in a concrete way. A single brand authorization letter may carry an effective scope and an expiry date; a product listing page may carry a category qualification description and a qualification upload date. In multilingual retrieval, the same document can be split into segments in different languages. Tracing a citation back to a source version requires that the cited text correspond to a specific document version and that the language segment not be treated as a separate authority.
The update frequency matters here only to the extent that a citation must resolve to the version in force at the time of the cited statement. The brief does not describe a batch synchronization or trade-triggered mechanism, and none is assumed.
Constraints at the citation tracing step
The knowledge base search node outputs cited content as an array, and the array length may be zero. A zero-length array means no content was found; the output path still runs. An empty array is not a workflow error termination.
The node can associate one or more knowledge bases that use the same vector model. Knowledge bases with different vector models cannot be associated together. This is an association condition, not a claim about what happens after a cross-model association is attempted; the check is to confirm the identifier and exclude non-matching bases.
Semantic retrieval and the minimum relevance setting operate on similarity filtering. They do not perform permission or entity isolation. A relevance score is not a category, entity, or permission filter, and it does not exclude unrelated businesses or unauthorized records. Retrieval is not authorization.
Hybrid retrieval uses semantic recall and full-text recall, then merges the two result sets through RRF. RRF is a fusion process, not an on/off switch. Rerank requires a model and must be enabled according to the settings; it produces a 0-1 score. Image retrieval requires image input and the corresponding model capability. Question optimization adds one model call before the formal retrieval. These conditions constrain tracing: a citation must map to a specific document version, and a similarity score cannot replace source verification.
Hypothetical paper test sample
The following fictional materials are used for this paper check. They do not refer to any real customer, company, or legal identity number.
Material text one: "Brand authorization letter (hypothetical number A-001) states: the authorizing party is a brand management company, the authorized party is a Tmall flagship store operating entity, the authorization period runs from January 1, 2025 to December 31, 2025, and the authorized scope is the Tmall platform in mainland China."
Material text two: "Product listing page (hypothetical number P-001) states: the product category is cross-border food, the qualification upload date is March 10, 2025, and the qualification is valid until March 9, 2026."
Draft sentence to be assessed: "The flagship store may still use brand authorization letter A-001 to publish cross-border food products after December 31, 2025."
Configuration and implementation checks
| Configuration item | Hypothetical starting point for this check | Reason for the choice and comparison method |
|---|---|---|
| Associated knowledge bases | Two bases using the same vector model: brand authorization materials base and product listing materials base | The documentation states that only knowledge bases with the same vector model can be associated together. Confirm the identifier first and exclude bases with a different vector model. |
| Search mode | Hybrid retrieval | The documentation states that hybrid retrieval uses semantic recall and full-text recall together, which suits queries containing numbers and proper nouns. |
| Citation upper limit | Hypothetical starting point of 3000 tokens for this check | The documentation controls the citation upper limit in tokens. Compare against another token value and observe the change in cited content length. |
| Minimum relevance | Hypothetical starting point of 0.5 for this check | The documentation states this value takes effect only in semantic retrieval or when result reranking is used. Compare against 0.3 and observe the filtered results. |
| Question optimization | Enabled | The documentation states it addresses unclear references. Compare against the disabled state and observe retrieval in multi-turn dialogue. |
| Rerank | Enabled, with an available ReRank model selected | The documentation states reranking produces a 0-1 score. Compare against results without reranking and observe the ordering change. |
Three common errors
- Treating retrieval results as authorization to act. The search node outputs a citation array, and its length may be zero. Cited content is not business authorization. When checking, use the subject, object, and effective scope in the source text, and do not treat a retrieval hit as an effective authorization.
- Treating the minimum relevance value as a permission filter. Minimum relevance filters low-relevance results only. It does not exclude unrelated businesses or unauthorized records. When checking, confirm whether the cited content comes from the target retrieval scope to which access rights exist.
- Treating an empty citation array as a workflow failure. The documentation states that an empty array means no content was found and the output path still runs. When checking, use an explicit paper input of an empty array to check the downstream design, and do not infer that a retrieval rule necessarily returns an empty result.
How to verify the setup
- Input material text one and material text two. Compare the dates in the draft sentence against the authorization period and the qualification validity period. If the draft sentence states that A-001 may still be used after December 31, 2025, while material text one states the authorization period ends on December 31, 2025, the draft sentence does not match the source text. Expected outcome: the draft sentence is not supported.
- Input material text two. Compare the qualification validity period on the product listing page against the time range in the draft sentence. If the qualification is valid until March 9, 2026, and the draft sentence does not mention the qualification validity period, the draft sentence lacks evidence on qualification validity. Expected outcome: pending verification.
- Input an empty citation array. Compare whether the downstream node continues to execute. If the downstream node handles the empty array and outputs content without citations, the empty-result handoff runs normally. Expected outcome: the empty array does not trigger an error termination.
The checks above rely on the hypothetical materials stated in full. They do not claim that any test, deployment, approval, or business action has occurred. Where a document field is not provided, the value remains unknown.