What the documents look like
Trade returns and claims work handles reverse logistics and responsibility determination after export. Materials arrive from customer email, quality inspection reports, customs systems, and insurance claim systems. Updates are irregular, once per case. The working documents include the return agreement, the claim letter, the quality report, and the return customs declaration. Contract and transaction material comparison requires placing materials that share the same business object, the same period, and the same field side by side. For example, the returned quantity in the return agreement and the nonconforming quantity in the quality report must point to the same batch before any comparison is meaningful. Materials appear as email attachments, scanned files, and system export files. Field naming is not unified, and one fact may be spread across several documents. A comparison conclusion depends on context completeness: a fragment missing its subject, object, status, or valid scope cannot support a judgment.
Three industry facts shape this step. First, the same business fact is often split across documents, so the comparison depends on whether the retrieved context actually contains the matching fields. Second, materials are scanned and exported in inconsistent formats, so field meaning must be checked rather than assumed from a label. Third, the claim process runs on responsibility determination, which means a comparison statement carries business consequences and cannot rest on a similarity score alone.
Constraints at the context limits step
The maximum context of a model limits how much content a single request can reference. The reply limit constrains answer length only; it is a separate matter from the full context window. The knowledge base reference limit is controlled by tokens, so a long single document may be truncated, and the content actually entering the context needs to be checked against the question sample. A large memory round count brings in unrelated materials, while too small a count loses earlier references. When a fixed reply format such as json_schema is used, complete fields and successful parsing require separate verification; normal text length does not mean the structure is usable. Semantic recall and relevance scores reflect content similarity only and do not perform permission or entity isolation. Whether a retrieval result can be used for comparison depends on whether the material itself falls within a retrieval scope the user has access to.
Hypothetical exercise sample: Material A is an excerpt from a return agreement stating "the buyer returned 120 units of batch A on 10 March 2025, with the reason recorded as surface scratches." Material B is an excerpt from a quality report stating "batch A sampled 30 units, of which 12 showed surface scratches." The draft sentence to be judged reads: "The return agreement and the quality report describe the returned quantity of batch A consistently, which can support the claim." In checking this draft sentence, Material A gives a total returned quantity, while Material B gives a sampled nonconforming quantity. The two fields carry different meanings, and the draft sentence treats different fields as the same field.
Configuration and implementation checks
The table below lists documented settings or implementation check items relevant to this page's function, organized around the sample above. The values are hypothetical exercise starting points chosen to make truncation observable; the comparison object is the actual input content of the same sample under different settings.
| Configuration item | Hypothetical exercise starting point | Check method |
|---|---|---|
| AI model maximum context | The value actually displayed for the selected model | Compare with the combined character count of Materials A and B to confirm whether it is exceeded |
| Reply limit | Enabled and set to a medium length | Compare with the length of evidence explanation the draft sentence requires, to observe truncation |
| Memory rounds | Retain a small number of history rounds | Compare the input for the same question with empty history and with history |
| Reference limit | Set an observable value by tokens | Compare with the length of a single material to confirm whether it is truncated |
| Minimum relevance | Keep the default | Observe the filtering effect only under semantic retrieval or result reranking |
| Reply format | Select json_schema when fixed fields are needed | Verify complete fields and successful parsing, not text length alone |
Three common errors
- Treating different fields as the same field. Material A records a total returned quantity, and Material B records a sampled nonconforming quantity. The draft sentence calls the quantities consistent. The input is the two source materials, the comparison is field meaning, and the observable result is that the draft sentence conflates two different fields.
- Treating a retrieval hit as permission or entity confirmation. The input is a semantically similar retrieval result, the comparison is whether that result falls within a retrieval scope the user has access to, and the observable result is that similarity alone cannot confirm the material is usable for this comparison.
- Treating a pending review request as granted authorization. The input is a handover request marked "pending review," the comparison is request status against execution status, and the observable result is that pending review does not equal approval and cannot advance a comparison conclusion.
How to verify the setup
- Input the source text of Materials A and B together with the draft sentence, compare whether the draft sentence treats the total returned quantity and the sampled nonconforming quantity as the same field, and the observable result is that the draft sentence is flagged as field-inconsistent and requires rewording.
- Input the same question under empty history and under history, compare the content actually entering the context in both conditions, and the observable result is that the memory round setting does change the input scope without introducing unrelated materials.
- Input an explicit paper-based empty result
[], compare how the downstream node is designed to handle an empty result, and the observable result is that the downstream follows the empty-result branch without asserting that a fictional rule retrieval always returns an empty array.