What the documents look like
Presale group-buy operations collect orders first and organize procurement and fulfillment afterward. The working materials are a presale product table, a group-order result, a procurement plan and an order-cutoff notice. These materials update daily or per session, so parsing and chunking must preserve document identity and version information that lets a retrieval result be traced back to a specific source file.
In cross-border and multilingual retrieval, the same batch of product tables may carry Chinese product names alongside foreign-language specification descriptions, and supplier inventory files may use different languages. A single product line can combine a specification, a minimum order quantity and a cutoff time as one constraint set. When such a set is split apart, a retrieved fragment loses the scope it was meant to apply to. The group-order result and the procurement plan also hold quantity relationships that should remain comparable after chunking. Language coverage of the vector model determines cross-language recall, while full-text retrieval depends on keyword matches and suits exact queries such as item numbers and model codes.
Constraints at the document chunking step
Segmentation completeness directly affects retrieval quality. Specifications, minimum order quantities and cutoff times in a presale product table belong to the same constraint condition; if they are separated, a single retrieved fragment no longer shows which product or period it governs. The group-order result and the procurement plan need a field structure that keeps quantities comparable across the two documents. Multilingual materials require attention to whether the vector model covers the languages present, and to whether full-text retrieval can match exact identifiers.
Hypothetical paper exercise sample: a platform operations staff member prepares a foreign-language supplier presale product table. The source text reads: "Item A-1024, frozen shrimp, net weight 1kg per bag, minimum order 200 bags, order cutoff 18:00 each Tuesday." In the same batch there is a Chinese cutoff notice stating that this week's cutoff time is adjusted to Wednesday 18:00. A draft sentence under review reads: "The cutoff time for A-1024 is Tuesday 18:00 each week, consistent with this week's notice." The sentence concerns the same item and the same time field, while the two materials give different values for this week's cutoff.
This sample is constructed for paper comparison only. No upload, training, deployment or approval has taken place.
Configuration and implementation checks
| Configuration item | Hypothetical starting point for this exercise | Reason and comparison method |
|---|---|---|
| Search mode | Hybrid retrieval | Covers natural-language questions about foreign specifications and exact item-number queries; compare against semantic retrieval alone |
| Reference limit | Set in tokens; starting value undetermined | Documents control reference volume by tokens; compare against actual recall at different chunk lengths |
| Minimum relevance | A 0-1 value; starting value undetermined | Takes effect only in semantic retrieval or with result reranking; compare against recall with the value disabled |
| Question optimization | Enabled or disabled according to observed effect | Can complete references in follow-up turns; compare retrieval results against the disabled state |
| Result reranking | Enabled when a model is available and configured | Reorders candidate text; compare ordering against results without reranking |
| Vector model | Must support the target languages | Cross-language recall depends on model capability; compare against a model without that language support |
The reference limit uses the documented token unit rather than a guessed item count. The minimum relevance value is a similarity threshold and does not act as an entity or permission filter; retrieval results still require separate business authorization checks. Hybrid retrieval combines semantic and full-text recall through RRF, which is a fusion step in the retrieval chain, not a switch to be turned on.
Three common errors
- Treating a successful upload as an updated retrieval index. After materials are uploaded, the actual training and indexing state needs verification. When training has not completed, retrieval may return empty results, and this should be recorded as pending verification rather than as a confirmed outcome.
- Treating the minimum relevance value as an authorization filter. This value filters by similarity and does not isolate entities or enforce permissions. A retrieved record still needs separate business authorization review before any downstream action.
- Judging two materials as contradictory on a time field without checking subject and period. The regular Tuesday cutoff for A-1024 and this week's adjustment notice cover different periods. Each needs its applicable scope marked before any comparison.
How to verify the setup
- Input the foreign-language source text and the draft sentence from the hypothetical sample, then compare the draft sentence against the time fields in both materials. If retrieval returns both materials and the draft sentence does not distinguish the regular value from this week's value, the draft sentence is unsupported.
- Input the item number "A-1024" in full-text retrieval and compare whether the returned content includes the specification and minimum order quantity for that item. If the returned content is missing the minimum order quantity field, segmentation completeness does not meet the comparison condition.
- Input the Chinese question about the frozen shrimp minimum order quantity and compare recall between semantic retrieval and hybrid retrieval. If semantic retrieval does not return the foreign-language material while hybrid retrieval does, record the observed language coverage. Do not state a conclusion about the model's capability boundary from this single observation.
These checks describe expected comparisons on paper. They do not claim that any test, deployment or approval has occurred. Where a document field was not provided, the value remains unknown.