What the documents look like
Payment risk work for cross-border standalone stores centres on card network disputes and receiving accounts. The materials handled here are chargeback notices, fraud order lists, invoices, and proof of delivery. These differ from parcel-status fulfilment data, because the review object is a dispute or a settlement account rather than a shipment milestone.
The supplied brief puts the update frequency at daily and per order. Where that frequency affects chunking, the practical consequence is that a chargeback notice, the related order record, the delivery proof, and the customer service email each need to keep an identity and version that can be traced back to the source text. A condition and the content it constrains must stay inside the same data group. If a reply deadline sits in one chunk while the order it governs sits in another, a later question about that order can miss the deadline entirely.
The official dataset engine description states that the smallest search unit is the library. A collection is a way to classify data and does not affect search results. This matters for product material and selection questions, because a question about a specific chargeback reason or order number is answered against the whole library rather than against a single collection.
Constraints at the document chunking step
Chunking follows the structure of the actual material. The chargeback reason, the deadline condition, and the corresponding order number belong in one data group. The dataset engine notes that one group of source data can map to several indexes, and that a leaner index raises precision while narrowing retrieval range. Full-text retrieval suits exact queries such as numbers, models, and error codes. Semantic retrieval suits natural language questions. Hybrid retrieval combines both and merges the paths through RRF. ReRank requires a model and runs according to the setting.
Retrieval and similarity affect recall and ordering only. They do not carry permission or entity isolation. Libraries built on different vector models cannot be associated together.
Hypothetical drill sample, for review only. Source text: "Notice number DN-2041, acquirer entity is a standalone store merchant, chargeback notice for order A-778, reason is goods not received, reply deadline is seven days after the notice is sent." A proposed draft sentence reads: "The chargeback for order A-778 has been fully handled and no reply is needed." The draft takes a value on the same field as the source deadline and is mutually exclusive with it. The draft is unsupported and stays pending verification. No real customer, company, or lawful identity number is used.
Configuration and implementation checks
The table below concerns the sample above. It lists only settings described in the official material or implementation checks. The values are hypothetical starting points for this drill, used to compare against neighbouring values. They are not official defaults.
| Setting or check | Hypothetical starting point | Reason and comparison object |
|---|---|---|
| Search mode | Hybrid retrieval | The sample contains number DN-2041 and a natural language reason; compare with pure semantic and pure full-text |
| Minimum relevance | Hypothetical start 0.3 | Compare with 0.2 and 0.5, observe whether unrelated fragments are filtered |
| Reference cap | Hypothetical start 2000 tokens | Compare with 1000 and 4000, observe whether the condition sentence is cut |
| Question optimisation | Left off for now | The sample question has a complete subject; compare with the enabled run and its added time |
| Result re-ranking | Enabled when a model is available | Compare ordering with the disabled run; executed according to the setting |
| Data and index check | Check training and index state | Confirm source data maps to its index; a successful upload does not mean retrieval is updated |
Three common errors
- Treating a successful upload as an updated index. Input: the upload record for the sample material. Comparison object: the training and index state. Observable result: whether a search for that material returns the corresponding content. Without that check the state remains unknown.
- Treating retrieval or similarity as authorisation. Input: the phrase "fully handled" in the draft sentence. Comparison object: the source reply deadline. Observable result: the draft and the source take mutually exclusive values on the same field, so the draft is unsupported.
- Describing hybrid retrieval as a switch, or treating re-ranking as always executed. Input: the search parameter settings. Comparison object: the RRF merge process described in the document and the stated condition for enabling re-ranking. Observable result: re-ranking runs only when a model is available and the setting enables it.
How to verify the setup
- Input the sample source text and the draft sentence. Compare "reply deadline is seven days after the notice is sent" with "no reply is needed". The observable result is that the draft is unsupported, and it is recorded as pending verification.
- Input order number A-778 as a full-text query. Compare whether the returned content contains that number together with the chargeback reason. The observable result is that a hit on the same source data group satisfies the check; a miss is recorded as a gap.
- Input an empty-result downstream case, using the paper input [] to check the downstream design. Compare whether the downstream handles it as empty input. The observable result is that no fabricated rule output is produced. This does not claim that retrieval always returns [].
A cross-model check comes first: confirm the library identifiers and exclude any that do not match, rather than running a cross-model search to compare missed recall. Where the material needed for a check is not present in an accessible target search scope or a defined manual input, the gap is recorded as a gap.