What the documents look like
Letter-of-credit document examination and presentation turns on documentary consistency. The service supports the bank's payment conditions, and the central question is whether the presented documents match the terms of the credit. The main materials are issuing-bank advices, UCP600 clauses, freight forwarder bills of lading, and bank presentation records. The daily documents are the credit, commercial invoice, bill of lading, insurance policy, and draft. These materials update per transaction, and document examiners, bank international settlement staff, and exporters all work with them.
The structure of these materials varies sharply. UCP600 clauses are general rule text. Bills of lading and insurance policies carry precise fields such as numbers, dates, and amounts. Presentation records capture time and status. Retrieval and recall must cover both rule semantics and document fields. Operating reports and exception reviews depend on accurate recall of historical presentation records and exception descriptions. A retrieval step that returns rule text when the review needs a specific bill-of-lading date, or that returns a different credit's record, undermines the review before any human reads it.
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 using different vector models cannot be associated together. Check the identifier first and exclude those that do not match; do not run cross-model retrieval to compare missed recall.
Search mode is compared against test questions. Semantic retrieval, full-text retrieval, and hybrid retrieval each have different strengths, and no single mode is presumed suitable for all materials. Full-text retrieval suits exact queries such as bill numbers, models, proper nouns, and error codes. Semantic retrieval suits natural-language questions and semantically close content. Hybrid retrieval uses both and merges results through RRF, which is a fusion process for mixed results and not an on/off switch.
The citation cap is measured in tokens. Test with actual materials of varying length to see whether content stays complete, then adjust the cap. The minimum relevance score is a value from 0 to 1 and takes effect only in semantic retrieval or when result reranking is used. Annotate relevant and irrelevant samples first, then tune the threshold. A relevance score is a filter threshold, not a category, entity, or permission filter; it does not exclude unrelated businesses or unauthorized records.
Question optimization performs coreference resolution and question expansion. Compare the original question with the optimized question and check whether the subject was altered. Reranking requires a rerank model and is enabled according to settings; it produces a 0–1 score. Image retrieval requires an actual image input and the corresponding model capability. The retrieval output is an array whose length can be zero, and the downstream path still runs when nothing is found. Retrieval and recall do not carry permission or entity isolation.
Hypothetical drill sample: Source text one reads "Issuing bank A advised credit LC-2024-001 on 1 March 2024, valid until 15 April 2024, latest shipment date 31 March 2024." Source text two reads "Bill of lading B, number BL-2024-088, on-board date 28 March 2024, port of loading Shanghai, port of discharge Hamburg." The draft sentence to be judged is "Presentation under this transaction is complete and collection proceeded without exception." The subject under review is the documents under LC-2024-001, the period is March 2024, and the fields are presentation status and collection status. The source texts do not state that presentation was completed or state a collection result. The draft sentence is unsupported and remains to be verified.
Configuration and implementation checks
| Configuration item | Hypothetical trial starting point for this page | Reason and comparison method |
|---|---|---|
| Associated knowledge bases | Select a credit-terms base and a presentation-records base that use the same vector model | Verify the vector model identifiers match before associating; exclude any that do not match |
| Search mode | Test semantic retrieval and full-text retrieval separately first | Compare full-text hits on bill-number questions with semantic hits on rule-explanation questions |
| Citation cap | Set to 800 tokens | Test with credit clauses and document fragments of varying length for content completeness, compared with smaller values for truncation |
| Minimum relevance score | Set to 0.4 | Annotate relevant and irrelevant samples first, then compare the proportion of irrelevant fragments entering citations at different thresholds |
| Question optimization | Enabled | Use multi-turn questions containing references and compare whether the subject stays consistent before and after optimization |
| Result reranking | Enabled according to settings | Where a rerank model is present, compare the ordering difference between rerank scores and vector scores |
The values above are hypothetical trial starting points for this page and are not official defaults. Image retrieval requires a corresponding image input and model capability. Reranking requires a model and is enabled according to settings.
Three common errors
- Treating a retrieval hit as authorization to act. Input: the draft sentence "Presentation under this transaction is complete and collection proceeded without exception." If a presentation-record fragment is retrieved and the conclusion is drawn that collection is complete, the comparison object should be the status field stated in the source text. The observable result is that the source text does not state a collection result, so the conclusion is unsupported. Retrieval does not carry permission or business-status confirmation.
- Associating knowledge bases that use different vector models. Input: two knowledge base identifiers. Compare whether their vector model identifiers match. The observable result is that identifiers that do not match must be excluded; do not run the associated retrieval, and do not infer any run-time result from associating them.
- Confusing pending review with approval. Input: a handover request whose status is pending review. Compare whether the source text states an approval action. The observable result is that when no approval is stated, the request remains pending review and does not constitute authorized execution.
How to verify the setup
- Use hypothetical source text one and source text two as retrieval input. Compare whether the recalled content includes the validity period of LC-2024-001 and the on-board date of BL-2024-088. The condition is met when the cited content contains the subject, object, and date fields together and does not mix in records of other credit numbers.
- Use the draft sentence "Presentation under this transaction is complete and collection proceeded without exception" as the object of review. Compare whether the source text states presentation completion and a collection result. The condition is met when the source text does not state them, in which case the sentence is judged unsupported and the evidence gap is recorded; it is not judged as a negation or a conflict.
- Use an empty array [] as the citation output to check the downstream design. Compare whether the downstream handles it through the empty-result branch. The condition is met when the path runs and produces no business action. Do not claim that a fictional rule retrieval necessarily returns [].
This page addresses only letter-of-credit document examination and presentation, operating reports and exception reviews, and knowledge base retrieval and recall. Whether materials, operations, or requests are in an authorized state during an operational handover is a separate question; retrieval or a form is not authorization to execute.