Data Characteristics for This Category
Registration and declaration regulatory documents in the biomedical field primarily originate from laws, regulations, departmental rules, technical guidelines, and approval announcements issued by the National Medical Products Administration (NMPA) and its subordinate agencies. These documents are mainly in PDF, Word, or HTML formats. Updates typically occur quarterly or annually, with unscheduled revisions released during significant policy changes. Document structures are rigorous, containing numerous clauses, detailed rules, appendices, and charts. Fields such as "registration classification," "declaration material items," "review timelines," and "fee standards" have clear definitions and standardized expressions. Units often involve time (days, months), quantity (copies, items), and percentages.
Constraints Imposed by These Characteristics on "Reference and Traceability"
The official and rigorous nature of registration and declaration regulatory documents requires references to precisely point to the original source. This ensures information authority and credibility. Their complex hierarchical structure and extensive specialized terminology make semantic understanding and information retrieval challenging, necessitating more refined text segmentation strategies. Although the update frequency is not high, each update can involve revisions or abolitions of key clauses. This requires the knowledge base to have version management capabilities and to promptly synchronize the latest official releases. Additionally, common tables and appendices in documents require special handling during information extraction to avoid losing important structured data and to ensure accurate citation of these details in responses.
Configuration Settings
| Configuration Item | Suggested Value | Rationale |
|---|---|---|
Chunk size (Chunk Size) | 300–500 characters (characters) | Registration and declaration clauses are logically tight; avoid splitting that breaks semantics. |
Recall count (Recall Count) | Top 10 entries (top 10) | Ensures coverage of different clauses and details of relevant regulations. |
Similarity threshold (Similarity Threshold) | 0.75–0.85 | Improves retrieval precision, avoiding interference from irrelevant clauses. |
Rerank result count (Reranked Return Count) | Top 5 entries (top 5) | Focuses on the most relevant content, improving answer quality. |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds (seconds) | Handles parsing of large PDF documents, preventing timeouts. |
maxContext | 8192 token | Accommodates longer regulatory texts, providing sufficient context. |
Common Pitfalls
- After a query, the model fails to extract content from the local knowledge base, provides a generalized answer, or has missing or inaccurate reference lists. This typically results from a
Similarity threshold(similarity threshold) set too high, causing slightly less relevant document chunks to be filtered out before the recall stage. - The text pointed to by the reference source does not completely match the answer content, or the reference is an outdated version. This often occurs when the knowledge base fails to promptly synchronize the latest regulatory revisions issued by the NMPA, or due to a lack of document version management.
- When asked about table or appendix content, the model's answer is incomplete or cannot cite specific data. This indicates that structured data was not effectively identified and extracted during document parsing, leading to its loss during vectorization.
How to Confirm Correct Configuration
- Query specific regulatory clauses and check if the answer accurately cites the corresponding clause number and original text. Compare the cited entries with the original document for consistency.
- Randomly select a newly published registration and declaration guideline, upload it to the knowledge base, and query it. Verify if the model can correctly identify and answer new or revised content within it.
- Query specific table data from regulatory documents (e.g., "review and approval timeline table"). Check if the model's answer includes correct values and units, and confirm that the reference source points to the table's location.
- Check system logs to ensure no file processing failures occurred due to file parsing timeouts during
PARSE_FILE_TIMEOUT_SECONDS.
The values provided are common starting points and should be measured against specific samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-21.