What this category of data looks like
Beneficial owner KYC data primarily comes from customer due diligence materials collected by financial institutions. These include corporate industrial and commercial public information, equity penetration forms submitted by customers, and related relationship statements. Data updates are triggered when the customer subject changes, or follows fixed cycles required by regulations. Documents take structured tables as their core, with a small amount of explanatory text attached. Fields include subject name, document type, document number, shareholding ratio, related relationship type, and employment status. Shareholding ratio is measured in percentage units. The data also includes identifiers for both natural persons and legal persons.
What constraints do these characteristics impose on vector models and indexing
Structured tables make up a large share of the data, and most fields are identity or numeric identifiers. Standard text chunking will split the associated relationships between fields. This requires support for structured table parsing and multi-vector storage. Numeric fields such as shareholding ratio need to retain precise semantics. General text embedding models tend to over-generalize, so adaptation to the encoding logic of structured fields is required. Data update timing is irregular, and the data involves sensitive identity information. The index must support incremental updates, and comply with data desensitization storage requirements.
How to set the configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
PARSE_TABLE_ENABLE | Enabled | Beneficial owner data takes structured tables as its core. Enabling this setting preserves the associated semantics between fields, avoiding chunking that splits equity hierarchy information |
MULTI_VECTOR_SUPPORT | Enabled | Adapts to the independent semantics of multiple fields within a table. Generates dedicated vectors for each field, improving recall accuracy for related subjects |
MAX_SEGMENT_LENGTH | 800–1200 characters | Beneficial owner documents often contain multi-layered equity information. This range balances semantic completeness and chunk granularity, avoiding lost context from overly long chunks or broken hierarchical associations from overly short chunks |
INDEX_DIMENSION | 1024–1536 | Matches the output dimensions of mainstream embedding models, adapting to the encoding needs of multiple types of fields for beneficial owners |
RECALL_TOP_K | Top 8–12 results | Beneficial owner verification requires coverage of multi-level related subjects. This range balances recall completeness and inference overhead |
SIMILARITY_THRESHOLD | 0.75–0.85 | Filters low-relevance non-beneficial owner information, avoiding incorrect recall of unrelated corporate background data |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require case-by-case analysis. It is recommended to test on samples tailored to the specific deployment before finalizing settings.
Three common configuration errors
- Symptom: After enabling table parsing in knowledge base settings, related fields still cannot be correctly recalled. Cause: The
MULTI_VECTOR_SUPPORTconfiguration was not enabled simultaneously. Enabling only table parsing preserves the table structure, but cannot generate independent vectors for fields. - Symptom: The knowledge base service operates normally, and a model is configured. New conversation tests work normally, but a "No available indexing model detected" error pops up after refreshing the page. Cause: The currently selected embedding model was not set as the indexing call model, or the model's output dimension does not match the
INDEX_DIMENSIONparameter configured for the knowledge base. - Symptom: An incomplete format return error occurs when accessing a multimodal embedding model. Cause: Multi-type field data for beneficial owners was not passed in the input format required by the model, leading to model interface call failure.
How to confirm the configuration is complete
- Review the knowledge base's vector model configuration page, confirm both
PARSE_TABLE_ENABLEandMULTI_VECTOR_SUPPORTare enabled. - Upload a standard beneficial owner document, check the chunking preview, confirm that table fields are fully preserved and not excessively truncated.
- Initiate a vector recall test, input a query containing shareholding ratio and related relationships, verify the field completeness and relevance of the recall results.
- Check the knowledge base index status panel, confirm that index generation progress is normal and no error logs are present.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-14.