What the documents look like
Multi-store matrix management for platform commerce involves brand e-commerce leads, channel operations staff, and distributor e-commerce teams. The daily materials include store authorization lists, price control tables, diversion complaint forms, and monthly sales reports. Cross-store authorization and price order are the main concerns in this category, and the materials often contain the same distributor's stores on different platforms, authorization scopes for different effective periods, and three field groups covering quotation, supply, and settlement. Document parsing and chunking must split these materials into segments that can be traced back to the source text, so that contract and transaction material comparison can check field by field.
A store authorization list may state an authorization object, an authorized platform, an authorization period, and an authorization scope. A price control table may state a distributor store, a model, a suggested retail price, and a quotation validity period. A diversion complaint form and a monthly sales report carry their own subjects, objects, periods, and statuses. Chunking must preserve subject, object, period, and status. A conditional clause and the provision it constrains must not be split into different segments. The same group of source data can map to multiple indexes, and during retrieval the vector score takes the highest score. The indexes field records vector IDs and is an array structure. Retrieval is a recall process and does not perform authorization judgment. A similarity score does not constitute a permission or entity filter. The citation limit is counted in tokens. The minimum relevance applies only during semantic retrieval or result reranking. Hybrid retrieval merges multiple result paths through RRF, and reranking requires a model and must be enabled according to settings.
Assumed exercise sample: the source text of a Regional Authorization Letter signed by a brand and Distributor A reads, "Authorization object: Distributor A; authorized platform: Platform A; authorization period: January 1, 2025 to December 31, 2025; authorization scope: East China offline stores and the Platform A flagship store." Another source text, a Price Control Table, reads, "Distributor A Platform A flagship store, a certain model suggested retail price 199 yuan, quotation valid until June 30, 2025." The draft sentence to be assessed is, "Distributor A supplies at 199 yuan on Platform A flagship store in August 2025." In this sample, the quotation validity ends on June 30, and whether the August supply still applies that price is not stated in the source text and remains to be verified.
Constraints at the document chunking step
Chunking for this task must keep the authorization period, the quotation validity period, the subject, and the object inside one traceable segment. When a segment loses the period field, a later field-by-field comparison cannot tell whether the draft sentence falls inside the authorized range. When a segment keeps only the price value and drops the validity period, the comparison loses the field that decides whether the price still applies. These are chunking outcomes, and they are separate from whether retrieval returns a result.
Retrieval itself does not establish authorization. A high similarity score does not mean a store is authorized, and the minimum relevance threshold does not exclude unauthorized stores or unrelated subjects. The citation limit controls how many tokens of content are cited per search, and it is not a top-k item count. When the vector store is PostgresSQL, the index is HNSW, and full-text retrieval uses MongoDB $text with jieba tokenization. Milvus 2.5.16 and above uses BM25. The search scope is the entire library; a collection is only for classification management and does not affect search results. Libraries built on different vector models cannot be jointly associated.
The document flow lists optional paths, and these do not all run on every request. Image retrieval requires a corresponding image input and model capability. Reranking requires a model and must be enabled according to settings. A pending request is not an approval, an offered option is not execution, and an unsigned termination is not a completed termination. A quotation validity period does not represent a supply period.
Configuration and implementation checks
| Configuration item | Assumed trial starting point for this page | Reason and comparison object |
|---|---|---|
| Search mode | Hybrid retrieval | Materials contain identifiers and natural language, so both query types need coverage |
| Citation limit | 2000 tokens | Compared with the full length of a single authorization letter, to avoid cross-segment truncation |
| Minimum relevance | 0.3 | Compared with 0.5, to observe whether valid segments are filtered out |
| Result reranking | Enabled | When candidate segments are numerous, filter by rerank score |
| Question optimization | Enabled for multi-turn follow-ups | Compared with the disabled state for continuous-dialogue retrieval effect |
| Chunking method | Split by clause boundary | Compared with fixed-length splitting, to check whether conditions stay complete |
The values above are assumed trial starting points for this page, not official defaults. Upload success is not the same as an updated index. After upload, the actual training and index status must be checked, and data whose training is not complete does not participate in retrieval. A form collects values; business verification, approval, database writes, and external synchronization require their stated downstream implementation.
Three common errors
- Treating upload success as an updated index. The input is the uploaded material and its stated training status; the comparison is between the upload record and the actual training and index status; the observable result is whether the material participates in retrieval. When training is not complete, the material does not participate, and this remains a gap rather than a retrieval failure.
- Treating a similarity score as a permission filter. The input is a query and its returned segments with scores; the comparison is between the returned segments and the authorization or subject fields in the source text; the observable result is whether unauthorized stores or unrelated subjects appear in the returned segments. The minimum relevance filters low-relevance results and does not exclude unauthorized stores or unrelated subjects.
- Treating a quotation validity period as a supply period. The input is the Price Control Table source text stating validity until June 30, 2025, and the draft sentence stating supply in August 2025; the comparison is between the quotation validity period and the draft supply month; the observable result is whether the source text states that the August supply still applies that price. The source text does not state this, so the matter remains to be verified and cannot be judged as a breach or conflict.
How to verify the setup
- Input the Regional Authorization Letter source text and the draft sentence. Compare the authorization period with the draft supply date. The condition is met when the retrieved segment contains the authorization period field and preserves the source condition. If the retrieved segment lacks the period field, chunking is incomplete.
- Input the Price Control Table source text and the draft sentence. Compare the quotation validity period with the draft supply month. The condition is met when the result presents both the quotation validity period and the supply date. If only the price value is returned and the validity period is lost, fields have been separated.
- Input the sample source text with an empty-result downstream scenario. Use the paper input [] to check the downstream design, and observe whether the downstream treats the empty result as unsupported. Retrieval does not guarantee a first-hit match or full recall. Libraries on different models cannot be jointly associated; check identifiers only and exclude those that do not match, without running a cross-model retrieval to compare missed recall.