What the documents look like
Export tax rebate filing takes place after goods leave the country, when tax vouchers are matched against what was declared. The main data sources are the electronic tax bureau, the export rebate filing system, customs electronic records, and the financial 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. This page addresses one task inside that category: inventory procurement and supplier records, with the document parsing and chunking step that supports it. Typical roles are foreign trade enterprise finance staff, tax accountants, and documentation clerks. Errors carry consequences that include delayed rebates, ineligibility for rebate, and tax risk. Records update monthly or per batch, so parsing and chunking must preserve a document identity and version that can point back to the original text, allowing the same batch of purchase invoices and supplier records to be located during later reconciliation.
Constraints at the document chunking step
Chunking must inspect paragraph completeness against the structure of each specific record, so that conditions, explanations, and the content they constrain are not separated. For a purchase invoice, the amount, the tax amount, and the corresponding supplier information belong in the same retrievable unit. Raw data and retrieval index are distinct: one group of raw data can correspond to multiple indexes, and one long text can map to multiple vectors, where a hit on any one vector recalls that data. Retrieval is a recall process and does not perform authorization decisions. A similarity score is not a category, entity, or permission filter. Semantic retrieval, full-text retrieval, and hybrid retrieval suit different situations; identifiers, model numbers, and proper nouns suit full-text or hybrid retrieval. Image retrieval requires image input and model capability, and reranking requires a model and must be enabled by configuration. The optional paths listed in the documentation do not mean every request executes all of them.
Hypothetical paper exercise sample: a foreign trade enterprise finance staff member obtains one purchase invoice in a given batch, whose text states "Supplier name: a certain East China trading company; goods name: cotton men's shirts; quantity: 1200 pieces; amount: RMB 84,000; invoice date: March 10, 2025; corresponding export customs declaration number: a certain number." A separate supplier record states "The supplier issued the above invoice on March 10, 2025, and the payment was received on March 15, 2025." The draft sentence to be assessed is "This batch of purchase invoices has completed matching with the export customs declaration and can be submitted for rebate filing." That draft sentence involves two business actions, completed matching and filing submission. The available material records only the invoice issuance and the receipt of payment, and does not record a matching result or filing authorization.
Configuration and implementation checks
| Check item | Hypothetical starting point for this exercise | Reason for the choice and comparison method |
|---|---|---|
| Search mode | Full-text retrieval | Purchase invoices contain exact identifiers such as invoice number and declaration number; compare hit differences against semantic retrieval |
| Reference limit | 2000 tokens as the hypothetical starting point | Estimated from document field lengths; compare against lower values to see whether key fields are truncated |
| Minimum relevance | 0.4 as the hypothetical starting point | Used to filter low-relevance fragments; compare against higher values to observe changes in recall count |
| Question optimization | Not enabled for this batch check | Document queries have clear subjects; compare elapsed time and hits against the enabled state |
| Result reranking | Not enabled for this batch check | Observe first when candidates are few; compare ordering changes against the enabled state |
| Image retrieval | No image input in this batch, not enabled | The sample is a text document; distinguish from scenarios with image input |
These values are hypothetical starting points for this exercise and do not constitute official defaults. The configuration covers search parameters and implementation check items only. Business verification, approval, database writes, and external synchronization require their own downstream implementation.
Three common errors
- Treating a similarity score as a permission or entity filter. The input is a retrieval request; the comparison is between the score and authorization fields; the observable result is that a high or low score does not change whether a supplier record falls within the current check scope, and authorization must be checked separately.
- Treating a successful upload as an updated retrieval index. The input is a record change action; the comparison is between upload status and the actual training and index status; the observable result is that a completed upload does not necessarily mean the new chunk can be recalled.
- Treating a pending review request as approved. The input is a draft sentence or a handover request; the comparison is between request status and approval records; the observable result is that pending review does not equal authorization, and when approval records are missing the finding is unsupported.
How to verify the setup
- Input the purchase invoice text and the draft sentence from the hypothetical sample, and compare the "completed matching" claim in the draft sentence against the invoice issuance and payment receipt facts recorded in the original text. The sentence is supported only when the original text explicitly records a matching result and filing authorization; otherwise record it as unsupported.
- Input identifiers such as the invoice number and the declaration number, and run full-text retrieval and semantic retrieval separately. Compare whether the target chunk is recalled under each mode, and observe the hit situation for identifier queries under full-text retrieval. A first-position hit or full recall is not assured.
- Input an empty-result follow-on scenario, using the explicit paper input
[]to check the downstream design. Compare whether the downstream handles it as an empty reference. No claim is made that a fictional rule causes retrieval to return[].
Libraries across different vector models cannot be associated together. Check identifiers first and exclude those that do not match, record the actual observation, and do not run cross-model retrieval to compare missed recalls. Retrieval checks describe observations and failure branches only, and do not assure that an unrelated query returns empty.
This page addresses only export tax rebate filing, inventory procurement and supplier records, and document parsing and chunking. During operational handover, the authorization status of materials, operations, and requests must be established separately; retrieval and forms do not constitute authorization execution.