What the documents look like
Letter-of-credit examination and presentation serves bank payment conditions, where consistency across documents is the central concern. This differs from export tax-rebate filing, which turns on tax matching. The working materials for a single transaction typically include the letter of credit, commercial invoice, bill of lading, insurance policy and draft. Sources include issuing-bank advice, UCP600 clauses, freight-forwarder bills of lading and bank presentation records. The material set changes with each transaction, and errors can lead to refusal, deductions or delayed receipt of funds.
For document parsing and chunking, each item needs a document identity and version that can be traced back to the source text. Segmentation should keep a condition, its explanation and the content it constrains within the same retrievable unit. In FastGPT, one group of source data can map to multiple indexes, and when vectors for the same group of source data are recalled, the vector score uses the highest score. During retrieval, vectors are recalled first, then the vector ID is used to find the original data in MongoDB; records corresponding to the same group are merged. If a letter-of-credit clause, invoice amount, bill-of-lading consignee, insurance coverage or draft tenor is split apart, the contract-and-transaction comparison loses the context needed for checking.
Constraints at the document chunking step
The following hypothetical paper exercise illustrates the constraints. It is clearly labelled as a paper exercise and has not been executed.
Hypothetical exercise sample: a letter of credit field 46A states "Shipment not later than 31 March 2025; bill of lading must show freight prepaid." The commercial invoice amount is USD 82,000. The bill of lading is marked "FREIGHT PREPAID." The insurance policy coverage is "ALL RISKS." A draft sentence under review reads: "This document set satisfies all terms of the letter of credit and may be presented." This sentence does not address the shipment date and freight-prepaid requirements of field 46A item by item, so the source text needs to be checked before any conclusion.
At the chunking step, the field 46A condition and the bill-of-lading date need to remain in the same chunk or in an associable group of source data. The invoice amount and the freight-prepaid marking need to remain traceable to their source text after segmentation. The chunking decision affects whether later comparison can locate the relevant fields together.
Configuration and implementation checks
| Configuration or check item | Value or action for this page | Basis and boundary |
|---|---|---|
| Search mode | Semantic search, full-text search or hybrid search selected by material type | Official documentation describes the differences among the three modes |
| Reference limit | Measured in tokens; a hypothetical starting value of 3000 is used for this paper exercise | Hypothetical starting value, chosen to compare reference completeness across chunking settings |
| Minimum relevance | A value from 0 to 1, effective only in semantic search or when result reranking is used | This value is a filtering threshold; it does not perform permission or entity isolation |
| Result reranking | Executed when a ReRank model is available and enabled by configuration | When not enabled, this path does not participate |
| Question optimization | Enabled as needed for multi-turn follow-up or short questions | The extra model call increases elapsed time |
| Post-update review | After material changes, check the actual training and index state | A successful upload does not indicate that retrieval has been updated |
Three common errors
- Splitting the letter-of-credit field 46A shipment date and the bill-of-lading date into different chunks, so the comparison cannot check them in the same segment. Check: input the field 46A source text and the bill-of-lading date field from the hypothetical sample above, compare whether the two fall into the same chunk or an associable group of source data, and observe whether the chunk boundary cuts the constraint relationship.
- Treating the minimum relevance value as a permission filter, assuming that low-scoring records are excluded means unrelated businesses are isolated. Check: input two groups of source data for different businesses in the same library, compare whether the retrieval return is determined only by relevance, and observe whether any records are excluded by business entity.
- Treating a successful upload as an updated index and skipping the training-state check. Check: input a changed invoice amount, compare the amount field returned by retrieval with the changed source text, and observe whether the returned content still shows the old value.
How to verify the setup
- Input the field 46A source text and the draft sentence from the hypothetical sample, compare whether the draft sentence covers the shipment date and freight-prepaid requirements item by item, and observe whether uncovered items are marked as pending verification. The condition is met when the draft sentence corresponds item by item to the source text, and unmatched points remain as gaps.
- Input the commercial invoice amount USD 82,000 and the bill-of-lading marking "FREIGHT PREPAID," compare whether the two can be traced back within the same group of source data, and observe whether both can be recalled after chunking. The condition is met when the two sets of fields can still be traced back to the source text after merging.
- Input the term "freight prepaid," the identifier "46A" and the natural-language question "when is the latest shipment date," search each separately, compare whether the returned chunks cover the corresponding fields, and observe the difference between full-text search and semantic search. The condition is met when all three input types can locate the chunk containing the field; when no hit occurs, the result is recorded as empty and the chunking setting is checked.
These checks are paper exercises and have not been executed. Retrieval or form submission does not constitute authorization; presentation, payment and refusal are business actions that require separate confirmation.