What the documents look like
Fresh-food weighing and sorting happens inside the warehouse fulfillment step, and the center of the work is weight and specification. The main data sources are the WMS, electronic scales, the order system, and quality-inspection photos. The documents handled day to day are sorting task sheets, weighing labels, short-weight compensation forms, and quality-inspection records. Data updates per order and per day.
In cross-border work these materials commonly mix Chinese, English, or several languages. A weighing label carries both numbers and specification abbreviations. A sorting task sheet carries both order numbers and product names. Document parsing and chunking has to split this material into retrievable fragments while keeping each fragment able to point back to the identity and version of the original document.
Three features of this category shape the chunking task. First, the documents are structurally different from one another: a sorting task sheet is built around line items, a weighing label is built around short fields, a short-weight compensation form carries conditional statements, and a quality-inspection record carries a conclusion plus a photo description. Second, the same original data can map to more than one index, so original data and retrieval index are separate concerns. Third, semantic recall and relevance scores affect ordering and filtering only; they do not carry permission or entity isolation.
Constraints at the document chunking step
The constraints come from differences in document structure. When segmenting, check the paragraph against the specific document structure and avoid separating a condition or explanation from the content it constrains. Keep original data distinct from retrieval index. Retrieval is not authorization.
Hypothetical paper exercise sample. The material text to be checked reads: "Sorting task sheet ST-2024-0517, in-warehouse batch B-03, product name chilled chicken thigh, specification 500g±20g, sorter Zhang San, date 2024-05-17. The weighing label shows net weight 498g, review status pending confirmation by the quality-inspection supervisor. Short-weight compensation form number BC-0517-02, application reason net weight below the lower specification limit, current status pending review." The draft sentence to be judged reads: "This batch has completed short-weight compensation and synchronized to the order system."
This sample is a paper exercise only. No test, deployment, approval, refund, or synchronization has occurred. The draft sentence is judged against the material text above.
Configuration and implementation checks
The table below lists only settings or implementation checks that this page's documents describe, tied to this feature and this task. Where a number is needed, it is a hypothetical starting point for this exercise, with the reason and the comparison method stated.
| Configuration item | Hypothetical starting point for this exercise | Reason and comparison method |
|---|---|---|
| Search mode | Hybrid search | Weighing labels carry numbers and specifications, so semantic and full-text recall are both used; compare number hit rate against semantic-only results |
| Reference limit | 800 tokens | Sorting task sheets and quality-inspection records differ greatly in length, so a token limit is steadier than top k; compare reference completeness against 400 and 1200 |
| Minimum relevance | 0.35 | Filters low-relevance fragments; compare the count of irrelevant fragments against 0.2 and 0.5 |
| Question optimization | Enabled | Completes references in multi-turn follow-ups; compare short-question recall against the disabled state |
| Result rerank | Enabled | Second-pass ordering when candidates are numerous; compare ranking position against the disabled state |
| Image retrieval | Check against ingestion index | Whether quality-inspection photos produced an image description or image vector index depends on model capability and ingestion state |
Hybrid search combines semantic recall and full-text recall through RRF, and RRF is a fusion process, not a switch. Minimum relevance applies only under semantic retrieval or when result rerank is used. The reference limit is measured in tokens. Image retrieval requires an image input and the corresponding model capability; it is not part of every request.
Three common errors
- Treating a successful upload as an updated retrieval index. After material changes, check the actual training and index state. Check: input the changed material and the old question, compare whether the returned fragment is the changed content, and observe whether an old version is still returned.
- Writing a pending-review status as a completed compensation. In the sample, the short-weight compensation form status is pending review, while the draft sentence says compensation is completed and synchronized. Check: input that compensation form text and the draft sentence, compare the status field, and observe whether the draft sentence matches the source status.
- Using semantic recall in place of a permission decision. Retrieval results do not distinguish authorization scope. Check: input the same question, compare returned fragments under different authorization scopes, and observe whether unauthorized records are mixed in.
How to verify the setup
- Input the sorting task sheet text from the sample and the question "What is the specification of ST-2024-0517?", compare whether the returned fragment contains specification 500g±20g and points back to that task sheet, and observe whether the fragment keeps the correspondence between number and specification.
- Input the weighing label text from the sample and the draft sentence "This batch has completed short-weight compensation and synchronized to the order system," compare the draft sentence against the compensation form status field, and observe whether the draft sentence agrees with "pending review." If it does not agree, record it as unsupported.
- Input the empty-result paper input [] together with the downstream design description, compare whether the downstream handles it as an empty result, and observe whether any description treats the empty result as a permission grant or as an automatic business action. Record that observation as pending verification.
Verification checks observe and record failure branches. They do not guarantee a first-position hit, full recall, or that an unrelated query returns empty. Where evidence is missing, it remains missing. A pending request is not approval, an offered option is not execution, and an unsigned termination is not a completed termination.