What the documents look like
Livestream sample selection and quality inspection happen before a broadcast, and the core question is whether a product can be sold and whether it suits on-camera presentation. Within the inventory procurement and supplier records task, the documents handled each week and for each product are sample evaluation forms, quality inspection reports, supplier qualifications and prohibited-sale lists. These come from supplier materials, testing-agency reports, platform negative catalogues and historical return rates.
Each document type carries identifying content that chunking must preserve. Supplier qualifications typically contain certificate numbers and validity periods. Quality inspection reports contain test items, conclusions and report numbers. Prohibited-sale lists contain platform rule entries. Sample evaluation forms contain trial records and assessment opinions. When a number, model, date or conclusion sentence is split apart, the retrieved fragment loses the subject and scope needed for cross-checking.
Constraints at the document chunking step
Chunking needs to retain document identity and version so a fragment can be traced back to its source. Conditions, test items and conclusions belonging to the same quality inspection report should sit in the same data block, so that a conclusion is not separated from the conditions that apply to it. Per the official description, one group of data can correspond to multiple vectors, and the indexes field records the corresponding vector IDs. A longer text can be given multiple vectors, and recall of any one of them recalls that data. For supplier qualifications containing numbers and validity periods, multiple indexes can be built around the same original document to raise block precision.
At the retrieval layer, semantic search relies on vector similarity, while full-text search relies on keyword hits and suits exact queries such as numbers, models, proper nouns and error codes. Hybrid search uses both and merges them through RRF. Minimum relevance is a filter threshold and takes effect only in semantic search or when result reranking is used; it does not perform permission or entity isolation. Retrieval is a recall process, and authorization status, approval conclusions and execution actions require a separate system implementation or manual cross-check.
Hypothetical paper exercise sample: a supplier submits a Sample Evaluation Form whose original text reads: "The submitted sample is a portable juicer of a certain model; the submission date is 10 March 2025; the assessment conclusion is that it may enter the trial broadcast stage; a copy of the supplier's business licence is attached, valid until August 2026." A draft sentence awaiting judgment reads: "The supplier's qualification is valid, the sample has passed quality inspection, and procurement and warehousing may be arranged." Comparing against the original shows that the sample records only the assessment conclusion of entering the trial broadcast stage. It records no quality-inspection pass conclusion and no procurement-and-warehousing authorization.
Configuration and implementation checks
| Check item | Relation to these documents | Hypothetical starting point and comparison method |
|---|---|---|
| Chunk completeness | Conditions and conclusions of sample evaluation forms and inspection reports need to stay in one block | Place a conclusion sentence and its applicable conditions in one data block, then compare against a split version to see whether the retrieved fragment can be traced to the original |
| Multiple indexes | Supplier qualifications contain numbers and validity periods, so multiple indexes can be built | Build multiple indexes for the same original document, then compare number-query hits against a single-index version |
| Search mode | Certificate numbers and models suit full-text or hybrid search | Run a number input through full-text search, then compare hit stability against semantic search results |
| Minimum relevance | This value is a filter threshold, effective only in semantic search or reranking | Set a hypothetical starting point of 0.3, compare against 0.5 for changes in the number of recalled fragments; the reason is to observe filter strength |
| Reference limit | Each search references at most n tokens of content | Set a hypothetical starting point of 2000 tokens, compare against 1000 to see whether referenced content covers the conclusion sentence |
| Post-update review | After materials change, actual training and index status need checking | After uploading a new qualification version, compare whether retrieval still returns old-version content |
Three common errors
- Treating a successful upload as retrieval already updated. After materials change, actual training and index status need checking; the upload action itself does not indicate the index has been rebuilt.
- Treating minimum relevance as permission or entity filtering. This value is a filter threshold and does not exclude unrelated businesses or unauthorized records; retrieval results still require manual verification of authorization boundaries.
- Treating a conclusion in a draft sentence as a fact from the original. The sample original records only entry to the trial broadcast stage, while the draft sentence adds a quality-inspection pass and procurement-and-warehousing authorization, which are unsupported extensions.
How to verify the setup
- Enter the sample original text and the draft sentence, then compare whether the draft sentence introduces a quality-inspection conclusion and warehousing authorization absent from the original. If the draft sentence contains a conclusion the original does not carry, that sentence is unsupported.
- Enter the certificate number through full-text search, then compare whether the returned fragment contains the number, validity period and subject. If the fragment lacks the validity period or subject, chunking is incomplete.
- Enter a query that is semantically similar but concerns a different subject, then compare whether the returned results contain records for another subject. If they do and no manual exclusion occurs, the relevance setting does not perform entity isolation, and manual cross-checking is required.
A pending-review status does not indicate an absence of operating permission. Signing, reaching cooperation and contract effectiveness are three distinct facts. Retrieval and forms collect values; business verification, approval, database writes and external synchronization require their stated downstream implementation.