What the documents look like
Export tax rebate filing happens after goods leave the country, and the work is matching tax vouchers to that export. The main data sources are the electronic tax bureau, the export rebate filing system, customs electronic information, and the finance ledger. The documents handled day to day are the export tax exemption and rebate filing form, the export customs declaration, purchase invoices, and foreign exchange receipt vouchers. The people doing this work are foreign trade company finance staff, tax accountants, and documentation clerks. When something goes wrong, the rebate is delayed, the rebate is denied, or a tax risk appears.
For copy drafting, the retrieval step pulls citable voucher information from these documents so that statements about goods, batch, and amount can be checked against source text. The update frequency is monthly and per batch. This page does not derive batch synchronization, full synchronization, real-time, or transaction-triggered mechanisms from that frequency.
Constraints at the retrieval step
The knowledge base search node can link one or more knowledge bases that use the same vector model. Bases with different vector models cannot be linked together. The identifier is checked first and non-matching bases are excluded; a cross-model search is not run to compare missed recalls. The same-vector-model requirement for the retrieval base does not extend to business registration sites or other external systems.
Cited content is output as an array and its length can be zero. Even when nothing is found, the output path still runs. Semantic retrieval, full-text retrieval, and hybrid retrieval are compared against test questions; no single mode is assumed to suit all materials. The citation limit is measured in tokens. The minimum relevance value takes effect only under semantic retrieval or when result reranking is used, and it is a filter threshold, not the final ordering rule. Question optimization handles reference resolution and question expansion. RRF is the fusion process for hybrid results. Reranking requires a model and must be enabled in settings; image retrieval requires image input and the corresponding model capability. Retrieval is not authorization, and semantic recall and relevance scores do not perform permission or entity isolation.
Hypothetical paper exercise sample: a foreign trade company finance staff member holds three source sentences. "Export customs declaration number A-2024-001, goods are stainless steel vacuum flasks, quantity 2,000 pieces, declaration date March 15, 2024." "Purchase invoice number B-2024-017, corresponding goods stainless steel vacuum flasks, quantity 2,000 pieces, invoice date March 10, 2024." "Foreign exchange receipt voucher number C-2024-009, amount corresponds to the above batch, receipt date April 2, 2024." The draft sentence to be judged is: "This batch of stainless steel vacuum flasks totals 2,000 pieces, completed export declaration in March 2024, and the related purchase and foreign exchange receipt vouchers are complete."
Configuration and implementation checks
| Configuration item | Hypothetical starting point for this exercise | Reason for the choice and comparison method |
|---|---|---|
| Linked knowledge bases | Link only one rebate material base that uses the same vector model | Check the vector model identifier first, exclude bases with a different model, then compare retrieval results |
| Search mode | Run the sample question with hybrid retrieval first | Compare against semantic retrieval alone and full-text retrieval alone, and observe differences on number-type and natural-language questions |
| Citation limit | Set the hypothetical starting point to a token amount that covers the three voucher source texts | Use the full sample source text as the reference and compare against a smaller value to see whether content is truncated |
| Minimum relevance | Set the hypothetical starting point to 0.5 | Label relevant and irrelevant fragments in the sample first, then compare filtering effects against adjacent values |
| Question optimization | The sample question already has a clear subject, so leave it off | Compare against the result with it on and check whether the subject is altered incorrectly |
| Result reranking | The sample has few candidates, so leave it off | Compare against the score ordering with it on and observe whether the citation order changes |
Three common errors
- Treating a semantic recall score as a basis for permission or entity filtering, so that a low score is read as excluding an unrelated business or an unauthorized record. Retrieval and authorization are separate matters, and access permission must be checked separately.
- Linking bases that use different vector models and then inferring missed recalls or redundancy from that link. The correct step is to check the identifier first, exclude non-matching bases, and record what is actually observed.
- Treating the phrase "vouchers are complete" in the draft sentence as already verified. The material states only the existence and dates of the three vouchers; it does not state a completeness conclusion, so that wording is unsupported.
How to verify the setup
- Input the three source sentences of the hypothetical sample and the draft sentence, then compare whether the quantity, goods, and date in the draft sentence match the customs declaration and purchase invoice source text. If the quantity or date differs, the draft is judged unsupported. If they match, the foreign exchange receipt voucher still has to be checked for coverage of the same batch.
- Input the draft sentence for retrieval and compare whether the returned citations include the three voucher source texts. If the return is an empty array, handle it as an empty result and check the downstream design. Do not claim that a rule-based retrieval necessarily returns empty.
- Input a paper document containing only the customs declaration, without the purchase invoice and foreign exchange receipt voucher, and compare whether the draft sentence "vouchers are complete" is supported. When the material is missing, record the evidence gap and judge the statement as pending verification.