What the documents look like
Permit processing happens before customs declaration and determines whether a shipment may lawfully cross a border. The working materials come from commerce authority systems, customs commodity codes, supplier documents and customer end-use statements. Day-to-day files include automatic import licences, dual-use item licences, contracts and product descriptions. These materials frequently carry product names, model numbers and end-use descriptions in both Chinese and English, so a Chinese question may need to match an English knowledge point. Cross-language semantic recall depends on the language coverage of the vector model and on the quality of the indexed content. The practical consequence is that the choice of vector model and the way indexes are built shape how reliably a compliance or customs reviewer can locate the right clause, code or status field. The eight-dimension brief marks its confidence as broadly accurate, so the background above remains conditional rather than verified for any specific operator.
Constraints at the vector indexes step
Knowledge bases joined in one retrieval must share the same vector model. The actual model and its input type are checked first; libraries built on different models cannot be associated together. The correct action is to inspect the model identifier and exclude non-matching libraries, not to run a cross-model retrieval and compare what is missed.
A single original data block may be linked to more than one index. Index content and original text are checked separately. Index content is best built from complete and focused information, and retrieval coverage against index length is weighed with the sample at hand. Image retrieval also depends on whether an image description index or image vector index was generated at ingestion time, not only on what happens at query time. Semantic retrieval and the minimum relevance score act only as similarity filtering; they do not perform permission or entity isolation, and retrieval does not constitute authorization.
Hypothetical paper exercise sample: the material text supplied for checking reads, "Automatic import licence application, applicant: Huaning Machinery Import and Export Co., Ltd. (hypothetical name); object: five CNC lathes; status is pending review; validity range: March 2025 to September 2025." The draft sentence to be judged reads, "The batch of CNC lathes has obtained an automatic import licence and shipment can be arranged." This sentence converts a pending-review status into an obtained one and is unsupported by the material. The material states no signing or effective clause, so that evidence gap remains open.
Configuration and implementation checks
| Configuration item | Hypothetical trial starting point | Reason and comparison method |
|---|---|---|
| Associated knowledge bases | Only permit and contract libraries sharing one vector model | Check model identifiers first and exclude non-matching libraries |
| Index content | One index per permit, segmented by product name, applicant and status | Compare segment by segment against the original text for coverage and length |
| Image index | Description index generated at ingestion for product description images | Inspect ingestion records to confirm the index was created |
| Search mode | Semantic retrieval plus full-text retrieval, merged through RRF | Compare full-text hits on model-number and code questions |
| Minimum relevance | 0.5 as the hypothetical trial starting point | Compare cited original text against 0.3 and 0.7 |
| Citation cap | 2000 tokens as the hypothetical trial starting point | Compare citation completeness against 1000 and 4000 |
The numeric values above are hypothetical trial starting points, not official defaults. RRF is a merge process for hybrid results and is not written here as a toggle. Image retrieval requires a corresponding image input and model capability; reranking requires a rerank model and must be enabled by configuration. The optional paths in the overall retrieval flow are not all executed on every request.
Three common errors
- Treating a pending-review status as an obtained permit. The draft sentence says the licence has been obtained, while the original text records pending review. The same applicant, the same permit and the same field carry mutually exclusive values, so the judgement is a contradiction.
- Associating knowledge bases built on different vector models. The input is two libraries with different model identifiers. After comparing the identifiers, the non-matching library is excluded and no cross-model retrieval comparison is run.
- Treating a retrieval hit as authorization. The input is a retrieved permit original text, and the comparison is against its status field. Pending review does not demonstrate that approval was granted; approval requires a downstream system implementation.
How to verify the setup
- Input the hypothetical original text and the draft sentence above, compare "has obtained" against "pending review", and the expected observation is that a contradiction is identified and marked for confirmation.
- Input a request involving two knowledge bases with different model identifiers, compare the model identifiers, and the expected observation is that the non-matching library is excluded and the actual observation is recorded, without producing a cross-model retrieval conclusion.
- Input an explicit paper empty result
[], compare the downstream citation chain design, and the expected observation is that the chain completes and no claim is made that a fabricated rule retrieval must return empty.
This page addresses only import and export permit processing, cross-border materials and multilingual retrieval, and vector models and indexes. Retrieval or a form is not authorization execution. Where a material, operation or request stands in an authorization state must be tracked separately in handover. Model or index changes are rechecked by comparing cited original text against the same set of questions, and no effect is promised from a vector score alone.