What the documents look like
Central chain procurement for cross-border materials revolves around centralized purchase contracts, replenishment plans, delivery notes and store requisition forms. The operational data comes from ERP purchasing, WMS, store POS and supplier delivery records, with daily or weekly updates. The main actors are the chain supply chain center, purchasing managers and distribution centers. Errors produce store stockouts, inventory accumulation or supplier claims.
The multilingual retrieval difficulty is that one centralized purchase contract may contain clauses in more than one language, and item names and numbers on delivery notes and requisition forms must correspond across language versions. The vector model and index handle semantic recall of these documents. A retrieval result by itself does not constitute any authorization or approval. Same-model association across knowledge bases is a documented requirement for vector search; it does not extend to requiring the same model in external systems such as business registration sites.
Constraints at the vector indexes step
Knowledge bases associated for retrieval must use the same vector model. Check the actual model identifier and input type first; knowledge bases using different vector models cannot be associated together. One original data block can be associated with multiple indexes. Index content and original text content are checked separately; the existence of an index does not establish that the original text has been confirmed. Indexes should be built from complete and focused information, and retrieval coverage against index length must be weighed against samples. Image retrieval also depends on whether an image description or image vector was generated at ingestion time; checking only the query side is insufficient.
Semantic recall and relevance scores do not perform permission or entity isolation. A similarity setting does not exclude unrelated business or unauthorized records. RRF is a fusion process for mixed results, not a switch that can be turned on. Empty result output is presented as an array, whose length can be zero, and the downstream chain still proceeds. Documented optional paths in the overall retrieval flow are not executed on every request: image retrieval requires corresponding image input and model capability, and reranking requires a model and must be enabled according to settings.
Hypothetical paper exercise sample: the following fictional materials are used for this paper check and do not refer to any real entity.
Material text one (centralized purchase contract excerpt): "Party A commissions Party B to supply the categories listed in the appendix to Party A's East China distribution center during the period from March 1, 2025 to August 31, 2025. The contract signing date is February 20, 2025."
Material text two (delivery note excerpt): "Delivery note number PS-2025-0312, shipment date March 12, 2025, recipient East China distribution center, item number SKU-4471, quantity 200 cartons."
Draft sentence to be assessed: "The centralized purchase contract took effect on February 20, 2025, and Party B must complete delivery of 200 cartons of SKU-4471 on March 12, 2025."
Configuration and implementation checks
The three columns below correspond to the check object involved on this page, the setting or implementation check already described in the official documents, and the starting point and comparison method for this hypothetical exercise. The values are starting points for this paper exercise only and are not official default values.
| Check object | Setting or check item | Hypothetical starting point and comparison method |
|---|---|---|
| Vector model | Associated knowledge bases must use the same vector model; check model identifier and input type | Starting point is one identical model identifier; compare character by character against the actual identifier of the associated knowledge base, and exclude that knowledge base if they do not match |
| Original data and index | One original data block can be associated with multiple indexes; index and original text are checked separately | Starting point is one original data record corresponding to two index groups; compare against the indexes field record in dataset.datas |
| Index content | Build indexes from complete and focused information; coverage and length must be weighed | Starting point is one complete contract clause index; compare against the recall result for the sample question and observe whether that clause is hit |
| Image index | Image retrieval depends on whether an image description or image vector was generated at ingestion | Starting point is that the delivery note image has a generated description index; compare against the query-side image input path to confirm both conditions |
| Version and result recheck | After a model or index adjustment, compare cited original text using the same set of questions | Starting point is one set of questions before adjustment; compare item by item against the cited original text for the same set of questions after adjustment |
| Citation limit | Each search cites at most n tokens of content | Starting point is the value set for this exercise; compare against the actual tokens of the returned cited content and observe whether the limit is exceeded |
Three common errors
- Forcing knowledge bases that use different vector models to be associated together. The input is two knowledge bases with different model identifiers; the comparison is between their respective model identifiers; the observable result is that the identifiers do not match. At that point the non-conforming one should be excluded and recorded, and no cross-model retrieval should be run to compare missed recalls.
- Using the existence of an index to infer that the original text has been confirmed. The input is the indexes field of a given original data block; the comparison is between index content and original text content; the observable result is that the index exists while the original text has not been checked. At that point they should be checked separately, and the index should not be treated as confirmation of the original text.
- Treating a pending-review state as already effective. The input is the phrase "took effect on February 20, 2025" in the draft sentence; the comparison is against material text one, which states only a signing date; the observable result is that signing and taking effect are different facts. At that point the evidence gap should be recorded, and no effective clause should be fabricated.
How to verify the setup
- Verification one: input material text one and the draft sentence; compare the draft phrase "took effect on February 20, 2025" against the original phrase "the contract signing date is February 20, 2025"; observe that the original text does not state an effective date. The condition is met when signing and taking effect are identified as different facts and the item is recorded as pending verification.
- Verification two: input material text two and the draft sentence; compare the draft phrase "must complete delivery of 200 cartons of SKU-4471 on March 12, 2025" against the original phrase "shipment date March 12, 2025"; observe that the original text states only a shipment date. The condition is met when shipment and completed delivery are distinguished and the evidence gap is retained.
- Verification three: input one set of questions together with cited original text before and after adjustment; compare the cited original text in the two rounds; observe whether the cited original text is consistent. The condition is met when differences are recorded item by item, and no effect is promised on the basis of vector scores alone.
Empty-result continuity can be checked on paper using the input array [] to review the downstream design, without claiming that a fictional rule retrieval necessarily returns []. Retrieval checks describe observations and failure branches, and do not guarantee a first-hit result, full recall or an empty result for unrelated queries.