What the documents look like
JD POP third-party store operations work around open-platform dispute rules and warranty-period service records. The daily materials include product information sheets, dispatch-time commitments, dispute handling forms, and warranty-period service records. For inventory procurement and supplier materials, these arrive as tables, commitment text, and correspondence records. A single supplier may correspond to several purchase orders, several versions of quotations, and arrival records for different batches. The brief states that material updates occur daily and per order. Chunking therefore has to keep content for the same supplier and the same procurement batch retrievable with a traceable identity and version back to the source text.
Constraints at the document chunking step
Chunking must preserve the subordinate relationship between a condition and the content it constrains. If the settlement method, delivery location, and acceptance standard in a purchase order are split into separate data chunks, retrieval may return only one of them, and a judgment about supplier materials would then lack a necessary premise. One group of source data can map to multiple vector indexes, so source data and retrieval indexes need to be recorded separately. After a material change, a successful upload does not mean actual training and indexing have updated; the training status has to be checked.
Hypothetical paper exercise sample: the source text reads, "Supplier A's March 2025 quotation states: Type A fitting unit price 12 yuan, quotation valid until 30 April 2025; delivery location is the registered warehouse of the JD POP store; acceptance standard follows the purchase order attachment." The draft sentence to be assessed reads, "Supplier A still supplies Type A fittings at 12 yuan in May 2025." The draft sentence concerns two different facts, the quotation validity period and the supply period. The material states only the quotation validity period and does not state the May supply price, so the draft sentence is unsupported.
Configuration and implementation checks
| Configuration item | Hypothetical trial starting point | Reason for the choice and comparison method |
|---|---|---|
| Search mode | Hybrid search | Supplier names and fitting models need exact hits, while procurement commitments need semantic matching; compare against semantic search alone |
| Reference limit | A starting value set in tokens | Purchase orders and commitment text differ greatly in length; compare result stability against a top-k approach |
| Minimum relevance | A starting value between 0 and 1 | Takes effect only in semantic search or with result reranking; compare recall range against filtering switched off |
| Question optimization | Enabled for multi-turn follow-up scenarios | Coreference removal in continuous dialogue can improve retrieval; compare first-turn hit results against it switched off |
| Result reranking | Enabled when candidates are numerous | Rerank produces a score from 0 to 1; compare against ordering by vector score alone |
| Full-text search | Implementation confirmed by vector database type | Number and model queries depend on keyword hits; compare hit results against semantic search |
The values above are hypothetical trial starting points for this exercise, not official defaults. The configuration items are configurable fields or implementation check items and do not include database internals.
Three common errors
- Treating the quotation validity period as the supply period. The draft sentence says supply continues at 12 yuan in May, while the material states only that the quotation is valid until 30 April. The check inputs the draft sentence and the source text, compares the "quotation validity period" field with the "supply price" field, and finds that the source text does not state the May supply price, so the support condition is not met.
- Treating a retrieval hit as authorization confirmation. Retrieving supplier material shows only that the content exists, not that a purchase has been approved. The check inputs a purchase request pending approval, compares the retrieval result with the approval status field, and finds that the approval status is not stated, so the confirmation condition is not met.
- Treating a successful upload as an updated index. After a material change, the actual training and index status must be checked. The check inputs the changed material, compares the upload record with the training status field, and finds that the training status does not show completion, so the condition for retrieval being updated is not met.
How to verify the setup
- Input the hypothetical sample source text and the draft sentence. Compare the period stated in the draft sentence with the quotation validity period in the source text. When the draft sentence falls outside the validity period and the source text does not state the price for that period, judge it unsupported.
- Input a supplier name and a fitting model, using full-text search and semantic search separately. Compare whether the two recall paths contain the corresponding data chunk, and observe whether the number-type query produces a hit.
- Input the changed material and compare the upload record with the training status. Observe whether the training status shows completion. If it does not show completion, record it as pending verification and do not judge that retrieval has updated. For an empty-result scenario, a clearly stated paper input of [] can be used to check the downstream design; do not claim that a fictional rule retrieval necessarily returns [].