What the documents look like
Price and display audits occur during ongoing operations, so the records are produced continuously rather than at a single opening stage. The working material consists of store visit photographs, price tag lists, display standards, and rectification notices, with updates arriving weekly or monthly. Chain operations staff, regional supervisors, and store managers handle these records.
Cross-border and multilingual conditions change the retrieval problem. One price tag list may exist in both Chinese and another language, a rectification notice may reference a head office promotion calendar, and a display standard may carry a version number and an effective period. Retrieval therefore has to locate a specific store, a specific promotion period, and a specific version among text and images that differ in language and source. The consequences of poor retrieval are customer price complaints, loss of brand standard control, and failed promotion execution.
Constraints at the retrieval step
The knowledge base search node can associate one or more knowledge bases that use the same vector model. Semantic retrieval supports cross-language understanding, so a Chinese question can match an English-language knowledge point, which suits price tag and display standard lookups across languages. Full-text retrieval depends on keyword hits and suits codes, model numbers, and proper nouns. Hybrid retrieval uses both vector and full-text recall, merges results through RRF, and then applies ReRank for a second ordering. The reference limit is measured in tokens. The minimum relevance value takes effect only under semantic retrieval or when result reranking is used. Question optimization performs coreference resolution and question expansion and adds one model call before retrieval. Image retrieval requires that a corresponding index was built at ingestion time and depends on a vision model or a vector model that accepts image input.
Retrieval returns content. It does not decide authorization, and it does not execute rectification or approval. A rectification notice whose status is pending store confirmation remains pending; a retrieved notice is not a completed rectification, and an offered option is not an executed action.
Assumed paper exercise sample. A regional supervisor submits a handover request for a pending decision, with the draft sentence: "This store's price tags match the head office calendar, so the case can be closed." The source material supplied for comparison reads: "Store A March 2024 price tag list, version V2, effective 1 March 2024 to 31 March 2024, subject Store A, object beverage price tags." "Head office promotion calendar notice, March 2024, beverages second item half price, applicable scope East China region directly operated stores." "Rectification notice, Store A, 12 March 2024, status pending store confirmation." A decision requires the same subject, the same period, and the same field. The material does not state whether Store A belongs to the East China directly operated scope, and it does not state whether the rectification is complete. The draft sentence's "match" and "can be closed" are therefore unsupported.
Configuration and implementation checks
| Configuration item | Assumed starting point for this exercise | Reason and comparison method |
|---|---|---|
| Associated knowledge bases | Select the price tag list base and the display standard base, both with the same vector model identifier | Compare the vector model identifiers first; exclude a base whose identifier differs and do not associate across models |
| Search mode | Run one round of semantic retrieval and one round of full-text retrieval | Use the same question to compare the two recall sets and observe the difference between price tag code queries and natural language queries |
| Reference limit | Assumed starting point of 2000 tokens for this exercise | Test with price tag lists of different lengths, compare whether the referenced content is complete, and adjust after comparison with shorter lists |
| Minimum relevance | Assumed starting point of 0.3 for this exercise | Label relevant and irrelevant samples first, then compare whether irrelevant fragments are filtered at different thresholds |
| Question optimization | Enabled for multi-turn follow-up, disabled for a single clear question | Compare the original question with the optimized question and check whether the store subject was altered |
| Result reranking | Enabled when candidates are numerous | Compare ordering before and after reranking and confirm the score can be used for filtering |
Three common errors
- Treating a retrieval hit as an authorization basis. In the assumed sample the rectification notice status is pending store confirmation. Retrieving that notice does not mean the rectification is complete, and it does not mean the case can be closed. For the check, input the notice text, compare the status field value, and observe whether it remains pending confirmation.
- Associating knowledge bases across different vector models. Assume the price tag list base and the display standard base carry different vector model identifiers while a joint association is still attempted. For the check, input the model identifiers of both bases, compare whether they are identical, and observe whether the mismatched base is excluded.
- Using a relevance threshold in place of subject verification. In the assumed sample it is not stated whether Store A belongs to the East China directly operated scope, and a minimum relevance filter does not resolve subject attribution. For the check, input the promotion notice's applicable scope and the store attribution material, compare the subject fields, and observe whether the attribution evidence is missing.
How to verify the setup
- Input the price tag list text and the draft sentence from the assumed sample. Compare whether the draft sentence's "match" is supported by evidence on the same subject, the same period, and the same field. Observe whether the judgment remains pending verification when the material does not state store attribution.
- Input the rectification notice text from the assumed sample. Compare the status field with the "can be closed" wording. Observe whether the pending confirmation status is misread as completed.
- Input the vector model identifiers of the two knowledge bases. Compare whether the identifiers are identical. Observe whether a mismatch excludes joint association and record the actual observation. For empty-result downstream handling, a paper input of [] can be used to check the downstream design; this does not assert that a fictional rule search must return [].
These checks describe what to compare and what remains unknown. No test, deployment, approval, refund, or other business action is claimed to have occurred.