What the documents look like
Short-video affiliate sales depend on long-lived content exposure and product-link conversion, so operations handovers are organized around four material types: short-video scripts, product lists for attached links, commission plans, and violation feedback. These materials update on a daily or per-order rhythm. A single product typically has several versions of its commission plan, and scripts reference product lists through identifiers.
Document parsing and chunking decide whether these materials can be recalled paragraph by paragraph. If a chunk boundary separates a commission rate from the product identifier it applies to, later comparison loses its basis. This page addresses one task only: contract and transaction material comparison for short-video affiliate operations, at the document parsing and chunking step. It does not construct business functions that lack a documented basis.
Constraints at the document chunking step
A knowledge base is organized into library, collection, and data. The smallest search unit is the library; collections only classify data and do not affect search results. A single data group can map to multiple vectors, and the indexes field records the corresponding vector IDs. When the same original data is recalled through several routes, the results merge and the highest score is taken. Retrieval first recalls vectors, then uses vector IDs to fetch original data from the dataset.datas table in MongoDB.
The reference cap is measured in tokens per search. The minimum relevance value is a filter threshold that takes effect only under semantic retrieval or result reranking; it is not a final ordering rule. Retrieval does not constitute authorization. A form collecting values is not the same as business verification, approval, or a completed database write. Those actions require their stated downstream implementation.
For this page, a hypothetical paper exercise sample is used. The source text of the commission plan to be checked reads: "Plan number JS-0417, applicable product SP-2201, commission rate 12%, validity range 2025-04-01 to 2025-04-30. This plan was submitted by operations; status is pending review." The source text of the product list for attached links reads: "Product number SP-2201, attached-link effective date 2025-04-05." The draft sentence to be judged reads: "The commission rate for SP-2201 on 2025-04-05 is 12%, already effective." The subject, object, and fields in this sentence can be aligned with the source text, but the source text states only a pending-review status.
Configuration and implementation checks
The values below are hypothetical starting points for this exercise, used to compare against another setting and observe differences. They are not official defaults.
| Configuration or check item | Hypothetical starting point | Reason and comparison method |
|---|---|---|
| Search mode | Hybrid retrieval | Identifier fields need full-text hits; natural-language descriptions need semantic recall. Compare recall differences against semantic retrieval alone. |
| Reference cap | 2000 tokens for this exercise | Sample material paragraphs are short. Compare against 1000 tokens to see whether the paragraph containing the commission rate is truncated. |
| Minimum relevance | 0.3 for this exercise | Takes effect only under semantic retrieval or reranking. Compare against 0.5 to observe candidate count changes. |
| Chunk boundary check | Keep product identifier and rate in the same segment | Check whether the rate sits in the same data chunk as the product identifier it constrains. |
| Index status check | Confirm training and indexing are complete | A successful upload is not evidence that retrieval has updated. |
| Identifier check | Record library and vector model identifiers | Libraries using different vector models are not jointly associated. |
Three common errors
- Reading a pending-review status as already effective. The sample source text states the plan status is pending review, while the draft sentence says "already effective." These are mutually exclusive values on the same field, which constitutes a contradiction. The check is to input the sample source text and the draft sentence, compare the status field values, and output a contradiction marker.
- Treating a retrieval hit as an authorization basis. Recalling a commission plan paragraph only shows that the paragraph is relevant to the query; it does not show that the operations party holds signing or execution authority. The check is to input a retrieval request, compare the returned content against authorization fields, and output a record stating "retrieval result contains no authorization information."
- Using a similarity setting to exclude unrelated records. The minimum relevance value is a filter threshold; it does not perform entity or permission isolation. The check is to input the same query while adjusting that value, compare the returned entries, and confirm that records not filtered out still require manual subject verification.
How to verify the setup
- Input the sample commission plan source text and the draft sentence. Compare the status field and the validity range field. If the draft sentence claims effectiveness while the source text says pending review, judge the claim as unsupported and record the evidence gap.
- Input the product number SP-2201 and a natural-language question, one at a time. Compare whether both recall results contain the rate and the identifier in the same segment. If either recall misses that segment, check the chunk boundary and the index status.
- Input a clearly labelled paper-based empty result. Check whether the downstream handling design distinguishes an empty result from "not retrieved." Do not claim that any invented rule necessarily returns an empty set.
These judgments preserve the authorization and effectiveness evidence gaps that the source text does not state. No clauses are supplied to obtain a definite answer.