What the documents look like
Platform product title and detail compliance handles advertising truthfulness and qualification display. It does not handle parcel delivery. The daily materials are product title tables, detail page assets, advertising prohibited-word lists, and third-party inspection reports. Sources are the platform rule center, advertising law compliance checklists, brand asset libraries, and inspection body reports. These materials commonly exist in Chinese, English, and target-market languages at the same time, so the title, parameters, and qualification wording of one product under different languages each need separate verification. The update frequency is weekly and on every new listing, so parsing and chunking results need to point back to a specific file and version for later verification to locate the original text.
For this task, the relevant facts are: materials arrive in multiple languages; the same product carries different wording across languages; and updates are frequent enough that a chunk must remain traceable to a file and version. These three facts shape how documents are parsed and split before retrieval.
Constraints at the document chunking step
After multilingual materials enter the knowledge base, the search unit is the library. A collection is only for classification management and is unrelated to search results. Semantic retrieval relies on vector distance and supports cross-language understanding, for example a Chinese question matching an English knowledge point, but precision depends on model training quality, keywords, and sentence completeness. Full-text retrieval relies on keyword hits and suits exact queries such as numbers, model numbers, and proper nouns. Hybrid retrieval uses both semantic recall and full-text recall and merges results through RRF. A Rerank model performs a second ordering of candidate text and produces a 0-1 score that can be used for filtering. The minimum relevance value takes effect only under semantic retrieval or when result reranking is used; it is a filtering threshold and does not carry permission or entity isolation duties. The reference limit is controlled in tokens, not top k, because in a mixed knowledge base the chunk lengths differ greatly and top k results become unstable. One group of original data can map to multiple vectors, and during retrieval, if any one of those vectors is hit, that group of data is recalled.
Hypothetical paper exercise sample: a product operations staff member submits material for ingestion. The original text is three sentences: "This product has a battery life of 12 hours, and charging for 30 minutes restores 80% of the battery. The applicable temperature range is 0°C to 40°C. This product has been tested by a third-party inspection body." In the same batch, one draft sentence awaits judgment: "This product lasts 12 hours, has received authoritative certification, and is suitable for all-weather use." There is also a handover request: "Please add the above material to the knowledge base and publish it externally." The material subject is the team of that product operations staff member. The object is the three original sentences and the draft sentence above. The state is pending ingestion, draft pending judgment, and publication request pending review. The effective scope is the current batch of that product. The authorization boundary is: ingestion and publication both require business review, and retrieval and forms do not constitute authorization execution.
Configuration and implementation checks
| Configuration item | Hypothetical starting value for this exercise | Reason and comparison object |
|---|---|---|
| Search mode | Hybrid retrieval | The material contains a Chinese draft sentence and English parameters, so semantic and keyword hits both need coverage; compared with semantic retrieval alone |
| Minimum relevance | 0.3 | Hypothetical starting value to filter low-relevance fragments; compared with 0.5 to observe recall count changes |
| Reference limit | 3000 tokens | Hypothetical starting value to cover multilingual paragraphs; compared with 1500 tokens to observe truncation |
| Question optimization | Enabled | The draft sentence contains a reference; compared with the disabled state for multi-turn follow-up effect |
| Result reranking | Enabled | Second ordering when candidates are many; compared with the disabled state for ordering stability |
| Image retrieval | Not enabled for now | This batch has no image input; compared with an image-bearing batch for applicable conditions |
Three common errors
- Treating a successful upload as retrieval already updated. The input is the just-uploaded material; the comparison object is the actual training and index state. If training has not completed, retrieval may return empty or old content. During checking, observe the training state field; if it is incomplete, record it as pending verification and do not judge it as effective.
- Using minimum relevance to exclude unrelated businesses or unauthorized records. The input is a cross-language query; the comparison object is the relevance score of returned results. That score is a filtering threshold and does not carry entity isolation. During checking, verify the source identifier of each returned item one by one; records outside the target scope should be excluded manually.
- Understanding the RRF merge after hybrid retrieval as an independent switch that can be turned on. The input is one hybrid retrieval request; the comparison object is the semantic and full-text recall results. RRF is a merge process, not a configuration item. During checking, inspect whether both recall paths executed; if only one path executed, record it as a condition not met.
How to verify the setup
- Input the three original sentences and the draft sentence from the hypothetical sample. Compare the draft sentence "has received authoritative certification, and is suitable for all-weather use" with the original text "has been tested by a third-party inspection body." The original text does not state a basis for "authoritative certification" or "all-weather." The draft sentence is unsupported and needs to be returned for supplementary evidence.
- Input the handover request "Please add the above material to the knowledge base and publish it externally." Compare the request state with the review state. The request is pending review and does not constitute publication authorization. During checking, observe the review record; if there is no review-passed record, the publication action must not be executed.
- Input the cross-language query "12-hour battery life." Compare the returned fragment with the original text "battery life of 12 hours." If the returned fragment contains that sentence and the source identifier matches, it is counted as a successful recall. If the return is empty, record it as an empty result and do not judge it as a missing rule. An empty result can be checked against downstream design using the paper input [].