What the documents look like
Category access on a platform happens before listing or merchant onboarding. The core materials are the business licence, trademark registration certificate, brand authorization chain, and industry licence. These materials often arrive as Chinese originals together with foreign-language translations, cross-border authorization letters, or multilingual versions. Across language versions of the same qualification, the subject name, registration number, and validity period need to remain checkable against each other. Materials are updated at irregular intervals, and each onboarding attempt may introduce a new layer in the authorization chain. The quality of document parsing and chunking directly affects whether later retrieval can locate the correct qualification fragment.
Structured licence documents carry fixed fields. An authorization chain is a layer-by-layer declarative text. A licence carries conditions and a permitted scope. During chunking, the document identity and version that allow a fragment to be traced back to the original must be preserved, and authorization conditions must not be separated from the authorization subject they constrain. Multilingual retrieval relies on the cross-language understanding of semantic retrieval; matching a Chinese question to a foreign-language qualification fragment is a documented advantage of semantic retrieval, and that capability depends on vector model training quality, so precision is not stable. The vector model identifier of the retrieval library must be checked first; libraries using different vector models cannot be associated together, so the identifier is checked and non-matching libraries are excluded. Semantic recall and relevance scores do not perform permission or subject isolation, and a retrieval result cannot be treated as an authorization status.
Hypothetical exercise sample: the material text supplied for checking consists of three sentences. Sentence one: "Authorizing party: Xingchen Stationery Manufacturing Co., Ltd.; authorized party: Blue Harbour Trading Co., Ltd.; authorized brand: Xingchen; authorized category: stationery." Sentence two: "Authorization period: 1 January 2024 to 31 December 2026." Sentence three: "This authorization letter is limited to Blue Harbour Trading Co., Ltd. for onboarding in the stationery category on Platform A, and sub-authorization is not permitted." A handover request awaiting determination: "Please confirm that Blue Harbour Trading Co., Ltd. may use the Xingchen brand to complete onboarding in the stationery category on Platform A, and that the authorization status is valid." The request involves five items of information: subject, brand, category, platform, and period. All five appear in the material text, but the authorization letter does not state a signing date or conditions of effectiveness. Signing, reaching cooperation, and contract effectiveness are three distinct facts. The authorization status in this request remains pending verification and cannot be determined directly from a retrieval result.
Constraints at the document chunking step
The business licence, trademark registration certificate, brand authorization chain, and industry licence differ clearly in structure, so a single chunking pattern cannot serve all four. Licence-type documents need their fixed fields kept together. The authorization chain needs its layer order preserved so that a condition is not detached from the party it binds. The industry licence needs its permitted scope kept alongside its attached conditions.
The document identity and version that allow a fragment to be traced back to the original belong in the chunk. Without them, a retrieved fragment cannot be attributed to a specific version of a specific material, and a later comparison against a translated version has no anchor.
Multilingual retrieval depends on semantic retrieval's documented cross-language capability. That capability is a property of the vector model and its training, and precision is described as unstable. Full-text retrieval suits exact terms such as registration numbers, model numbers, and proper nouns. Mixed retrieval combines both through RRF, and reranking can reorder text candidates. None of these paths performs permission filtering or subject isolation. A relevance score is a filtering threshold, not a final ordering rule, and it does not exclude unrelated businesses or unauthorized records.
The vector model identifier of each library must be checked before any cross-library comparison. Libraries built on different vector models cannot be associated together. This check is limited to the identifier; it does not extend to business registration systems or other external systems.
Configuration and implementation checks
| Configuration or check item | Setting or action relevant to this page | Relation to the hypothetical sample |
|---|---|---|
| Search mode | Semantic retrieval, full-text retrieval, or mixed retrieval, chosen as documented | Brand name and category name suit full-text retrieval; authorization conditions suit semantic retrieval |
| Minimum relevance | A 0-1 value, effective only in semantic retrieval or with result reranking | The hypothetical exercise starting value is 0.5, chosen because qualification fragments are semantically concentrated, and compared with 0.3 to observe the change in recall range |
| Reference limit | The maximum number of tokens cited per search | The authorization chain is long, so whether the cited content covers the authorization period sentence needs observation |
| Question optimization | Coreference resolution and question expansion before retrieval, which adds processing time | May be enabled for multilingual follow-up turns, and disabled for already explicit questions |
| Vector model identifier | Check the vector model used by the library; different models cannot be associated together | Confirm the qualification library and the retrieval request use the same vector model identifier |
| Training and index status | After upload, the actual training and index status must be checked | After an authorization letter is updated, a successful upload is not evidence that retrieval has been updated |
Three common errors
- Treating a successful upload of an authorization letter as retrieval already updated. Upload, training, and index status are separate stages and are checked separately. Check method: input the date from the authorization period sentence, compare whether the returned fragment contains that date, and observe whether content from an older version appears.
- Treating a semantic retrieval score as a judgment of authorization validity. The relevance value is a filtering threshold and does not perform subject, category, or permission filtering. Check method: input the handover request awaiting determination, compare whether the returned fragment contains the authorized party and authorized category fields, and observe whether any correspondence exists between the score level and the authorization status.
- Treating the RRF-merged result of mixed retrieval as a single vector ordering. RRF is a fusion process, and the final cited content may come from multiple recall paths. Check method: input the brand name and category name, compare the fragments returned by semantic retrieval and by full-text retrieval respectively, and observe whether the fused cited content contains both sources.
How to verify the setup
- Input the authorizing party and authorized party names from sentence one of the hypothetical sample, compare the subject fields of the returned fragment, and observe whether the same original authorization letter is located. If the returned fragment lacks the subject fields, record this as unsupported.
- Input the start and end dates of the authorization period from sentence two of the hypothetical sample, compare whether the returned fragment contains the complete period range, and observe whether the period sentence and the authorization subject sentence belong to the same data group. If the period sentence is recalled alone without the subject, record this as a chunking completeness issue.
- Input the platform and category restriction from sentence three of the hypothetical sample, compare whether the returned fragment contains the statement that sub-authorization is not permitted, and observe whether that condition sits in the same cited content as the authorization scope. If the condition sentence is absent, record this as an evidence gap.
If retrieval returns an empty result, an explicit paper input [] can be used to check the downstream design; it cannot be claimed that a fictional rule retrieval necessarily returns an empty array. Image retrieval requires a corresponding image input and model capability, and reranking requires an available model enabled by configuration. The optional paths shown in the overall document flow diagram do not mean every request executes all of them.