What the documents look like
Inbound receiving and putaway handles the first physical-versus-record confirmation when goods enter the warehouse. The main data comes from WMS, ERP procurement, supplier delivery notes, and barcode scanning. Day-to-day documents are the purchase arrival note, the inbound acceptance note, the putaway task, and the discrepancy report. Material updates occur per batch and per day. This page checks the chunking step at the point when the material actually changes; it does not infer batch synchronization or real-time triggers.
Document parsing and chunking faces three material types. The purchase arrival note carries the purchasing entity, supplier, item number, arrival quantity, and batch. The inbound acceptance note carries the received quantity, acceptance status, and acceptance signer. The putaway task carries the target location and execution status. The discrepancy report carries the discrepancy quantity, reason category, and handling status. These fields determine whether a chunk can point back to the source text, whether item number or document number can be searched precisely, and whether the purchase, acceptance, and putaway information for one batch stays together.
Constraints at the document chunking step
Segment completeness requires that a condition, its explanation, and the content it governs remain in the same data block. One data group can map to multiple vectors; when any one vector is recalled, that original data group is recalled. This gives a way to annotate longer text. Original data is stored in MongoDB dataset.datas, where the indexes field records vector IDs. Vectors are stored in the PostgresSQL vector field. Retrieval recalls vectors first, then uses the vector ID to fetch the original data from MongoDB; when the same original data group is matched, the highest score is taken. Knowledge base search operates at the library level; a collection is only for classification management.
Hypothetical paper test case: one batch of inbound material at an e-commerce warehouse. The source text reads: "Purchase arrival note PO-2024-0312, supplier A, item SKU-8841, arrival 120 units, batch B2403. Inbound acceptance note YS-0312-07 records received 118 units, acceptance status pending review, acceptance signer unsigned. Putaway task SJ-0312-19 target location A-03-02, status pending execution." The draft sentence to be judged is: "This batch of SKU-8841 has completed acceptance and has been put away to A-03-02."
Configuration and implementation checks
| Check item | Practice on this page | Observation and boundary |
|---|---|---|
| Material identity | Record document number, item number, batch, version | Chunks keep identifiers that point back to source text |
| Segment completeness | Condition and governed content in one block | Check that acceptance status and quantity are not split apart |
| Data and index | Distinguish original data from index | One original data group can map to multiple indexes |
| Retrieval mode | Search terms, numbers, and natural language separately | Number-type queries use full-text or hybrid retrieval |
| Reference limit | Set a hypothetical starting point in tokens for this batch | Compare with actual returned volume for the same batch questions |
| Minimum relevance | A 0-1 value, effective only in semantic retrieval or with rerank | A filter threshold, not a sorting rule |
The reference limit is controlled in tokens. The hypothetical starting point for this batch is 2000 tokens. The reason is that the four documents for this batch are short in total, and the value should be compared with the actual reference volume after retrieval before adjustment. This value is a trial starting point, not an official default.
Three common errors
- Treating a successful upload as proof that retrieval has updated. The input is a retrieval request after material changes; the comparison object is the actual training and index state; the observable result is that pre-change content is still recalled.
- Reading pending review or pending execution as already completed. In the sample, acceptance status is pending review and the putaway task is pending execution. The draft sentence states completed acceptance and completed putaway. The same field holds mutually exclusive values, so the draft is unsupported.
- Treating minimum relevance as a permission or entity filter. The input is a cross-supplier retrieval request; the comparison object is whether returned content includes unauthorized records; the observable result is that a relevance setting does not carry authorization duty, and retrieval does not constitute authorization.
How to verify the setup
- Input the sample source text and the draft sentence. Compare the acceptance status field values. The draft sentence is supported only when the source text contains an explicit record of completed acceptance and completed putaway. This sample shows unsupported.
- Input item number SKU-8841 and document number PO-2024-0312 as separate searches. Compare whether the returned block contains the corresponding identifier and batch. If the returned block lacks the batch or quantity, record it as a segment gap.
- Input a natural language question about the arrival quantity for this batch. Compare whether the returned content matches the source text value of 120 units. If it returns a quantity from another batch, record it as a recall scope issue. For the empty-result case, use the paper input [] to check the downstream handling design; do not claim that a fictional rule must return empty.
This page addresses only e-commerce warehouse receiving / procurement and supplier material / document parsing and chunking. During operational handover, the authorization state of materials, operations, and requests must be kept distinct; retrieval or a form does not constitute authorized execution.