What the documents look like
Letter-of-credit document examination serves the bank's payment conditions, and its central question is consistency across documents rather than tax matching. The material set for the inventory procurement and supplier records task therefore extends beyond the letter of credit, commercial invoice, bill of lading, insurance policy and draft. It also brings in purchase contracts, supplier lists and inventory batch records, so that document examiners can check whether the goods description, quantity, amount and supplier entity agree across the file. Principal data sources are the issuing bank's advice, UCP600 clauses, the freight forwarder's bill of lading and bank presentation records. The file is updated per transaction. Retrieval configuration has to accommodate exact fields such as document number, supplier name and batch number alongside natural-language description. The consequences of error are refusal to pay, deductions and delayed collection of foreign exchange, so retrieval output functions as a checking lead and does not replace an authorization determination.
Constraints at the retrieval step
The knowledge base search node can associate one or more knowledge bases that use the same vector model. Knowledge bases built on different vector models cannot be associated together; the model identifier is checked first and non-matching bases are excluded, without running a cross-model search in order to compare missed recalls. Search mode is compared across semantic, full-text and hybrid retrieval against test questions, and no single mode is presumed suitable for all material. The citation limit is measured in tokens; actual material of differing lengths is used to test whether content stays complete before the limit is adjusted. Minimum relevance takes effect only in semantic retrieval or when result reranking is used, and relevant and irrelevant samples are labelled before the threshold is tuned. Question optimization performs coreference resolution and question expansion; the original question and the optimized question are compared to check whether the subject was altered incorrectly. RRF is a fusion process for mixed results and is not a switch. Image retrieval requires a corresponding image input and model capability, and reranking requires an available model and must be enabled according to settings. An empty result is output as an array whose length may be 0, and the output path still runs. Retrieval and similarity scores do not perform permission or entity isolation.
Configuration and implementation checks
The table below lists check items relevant to this feature and the primary task, organized around a hypothetical paper exercise sample. Sample: an exporter presents documents to a bank, and the material contains letter-of-credit clauses, a commercial invoice, a bill of lading, an insurance policy, a draft and a supplier list. The sentence to be assessed is "The quantity of this batch of goods is consistent with the letter of credit, and the supplier has completed delivery." The hypothetical source text is: "The letter of credit stipulates a quantity of 1000 pieces, with a 5% tolerance for over- or short-shipment. The commercial invoice states a quantity of 1020 pieces. The bill of lading states a quantity of 1020 pieces. The supplier list states that the supplier for this batch is Company A, and the delivery status is shipped." This sample is a paper exercise and does not refer to a real customer or company.
| Configuration item | Hypothetical starting point for this exercise | Reason for the choice and comparison method |
|---|---|---|
| Associated knowledge bases | Associate only the document-examination knowledge base that uses the same vector model | Check the vector model identifier and exclude bases on different models |
| Search mode | Hybrid retrieval | Test numbered and natural-language questions together and compare recall differences |
| Citation limit | Hypothetical starting point of 800 tokens | Test content completeness with long and short material and compare against a shorter limit |
| Minimum relevance | Hypothetical starting point of 0.3 | Label relevant and irrelevant samples and observe changes in results after filtering |
| Question optimization | Enabled | Compare the original question with the optimized question and check whether the subject was altered incorrectly |
| Result reranking | Enabled according to settings | Confirm the model is available and observe rerank scores and ordering changes |
Three common errors
- Treating retrieval output as an authorization basis. Retrieval returns cited content only and does not determine whether a supplier is authorized or whether a contract has taken effect. The input is "the supplier list states that Company A has shipped"; the comparison object is the authorization document. If the authorization document does not state this, the point is unsupported and authorization cannot be determined.
- Forcing association of knowledge bases on different models. The input is two knowledge base identifiers on different vector models; the comparison object is the model identifier field. If they do not match, the base is excluded, no cross-model search is run, and no missed recall or redundant result is inferred.
- Treating minimum relevance as an entity filter. The input is an unrelated supplier record; the comparison object is the relevance score. A score below the threshold indicates insufficient relevance only and does not mean the supplier was excluded by permissions.
How to verify the setup
- Input the hypothetical source text "The letter of credit stipulates a quantity of 1000 pieces, with a 5% tolerance for over- or short-shipment. The commercial invoice states a quantity of 1020 pieces. The bill of lading states a quantity of 1020 pieces." Compare the sentence to be assessed, "The quantity of this batch of goods is consistent with the letter of credit," and observe whether the invoice and bill-of-lading quantities fall within the tolerance range. If they fall within the range, quantity consistency is supported; if they exceed it, it is unsupported.
- Input the hypothetical source text "The supplier list states that the supplier for this batch is Company A, and the delivery status is shipped." Compare the sentence to be assessed, "the supplier has completed delivery," and observe whether "shipped" and "completed delivery" belong to the same field and the same status. If the source text does not state that delivery is complete, the point is unsupported and pending verification.
- Input the hypothetical request "Please confirm whether Company A is authorized to present documents," and compare against the authorization document. If the authorization document does not appear within the accessible retrieval scope, record the evidence gap and do not determine that authorization exists. Check the empty result as the array [] against the downstream design, without asserting that a search of a fictional rule necessarily returns [].