What the documents look like
Store count and loss control work centers on book-to-physical variance and shrinkage. It does not handle supplier settlement. The material comes from POS inventory, WMS, monitoring systems, and count standards. Day-to-day documents include count sheets, variance analyses, damage write-off approvals, and monitoring retrieval records. Count sheets typically group SKU, storage location, book quantity, physical quantity, and variance quantity together. Variance analyses cite specific SKUs and responsible stages. Damage write-off approvals carry approval status and effective scope. These materials update monthly or quarterly. Parsing and chunking must preserve the correspondence among SKU number, store scope, count period, and status fields so that selection questions can refer back to the same source document.
Constraints at the document chunking step
Within a single count sheet, conditions, notes, and the SKU rows they constrain can be split apart, causing variance reasons and responsible stages to be mismatched. Source data and retrieval indexes require separation: one group of source data can correspond to multiple indexes, and adding indexes does not change source-data ownership. Terminology, SKU numbers, and natural-language phrasing differ in sensitivity to segmentation. Number-type queries depend more on full-text hits, while natural-language phrasing depends more on semantic recall. After a material change, upload success and retrieval updated are two separate states; actual training and index status require checking. Retrieval finds candidate content and does not perform permission or entity isolation. Libraries using different vector models cannot be jointly associated; check identifiers first and exclude non-matching ones.
Hypothetical drill sample
The following is a hypothetical drill sample and does not come from a real customer or system record. Source text: "Store A March 2025 count sheet: SKU 1023 book quantity 120 units, physical quantity 108 units, variance 12 units, variance reason field reads 'pending verification', count status is 'count complete'." Proposed judgment sentence: "The 12-unit variance for SKU 1023 has been confirmed by a damage write-off approval, and the responsible stage is receiving." Handoff request to check: "Please update the above variance reason to confirmed and synchronize to the inventory ledger." The source text gives only the variance quantity and the pending-verification status. It does not state a damage write-off approval number, an approval result, or a responsible stage. The proposed judgment sentence and the handoff request both lack source support.
Configuration and implementation checks
| Configuration or check item | Use on this page | Basis and boundary |
|---|---|---|
| Search mode | Choose full-text or hybrid for terminology and number questions; choose semantic or hybrid for natural-language phrasing | The official document lists semantic, full-text, and hybrid modes |
| Reference cap | Controls the number of tokens referenced per search | The official document uses tokens as the unit and does not use top k |
| Minimum relevance | Filters low-relevance results | Takes effect only in semantic retrieval or with result reranking |
| Result reranking | Reorders candidate text and filters by score | Requires a rerank model enabled per settings |
| Question optimization | Handles references and expansion in multi-turn follow-ups | Adds one model call before formal retrieval |
| Training and index status check | Confirms actual retrieval state after a material change | Upload success does not equal retrieval updated |
Hypothetical trial starting point for this page: set minimum relevance to 0.3. The reason is that the sample question is short and contains a number, and the aim is to observe whether SKU rows remain after filtering. Compare with 0.5 and observe the change in hit count for number-type questions. This value is a hypothetical starting point for this drill and is not an official default.
Three common errors
- Treating upload success as retrieval updated. Input is the changed count sheet. Compare upload status with training and index status. Observe whether retrieval returns old segmented content.
- Treating retrieval results as permission or entity isolation. Input is a cross-store question. Compare returned content with the store scope field. Observe whether SKU rows from other stores appear.
- Reading a pending-verification status as confirmed. Input is the sample source text and the proposed judgment sentence. Compare the variance reason field with the approval field. Observe whether the proposed judgment sentence obtains source support.
How to verify the setup
- Retrieve SKU 1023 using the sample source text. Input is "SKU 1023 variance reason." Compare whether the returned segment preserves the SKU, period, and status fields. Observe whether the variance reason remains pending verification.
- Check against the proposed judgment sentence. Input is "the 12-unit variance has been confirmed by a damage write-off approval." Compare whether the source text states an approval number and approval result. Observe whether the sentence is marked as unsupported.
- Check against the handoff request. Input is "update the variance reason and synchronize the inventory ledger." Compare the source text authorization scope with the requested action. Observe whether it is recorded as pending verification and not treated as executed. An empty result can be checked against an explicit paper input [] for downstream design; do not claim that a fictional rule necessarily returns [].
This page addresses only store count and loss control / product material and selection questions / document parsing and chunking. During operational handoff, which materials, operations, and requests sit at what authorization state cannot be treated as authorization execution through retrieval or forms.