Document Parsing and Chunking for Sanctions List Screening

Data characteristics for this use case

The primary data sources for sanctions list screening used in KYC and anti-money laundering work include public sanction lists published by regulatory authorities, politically exposed person (PEP) lists, suspicious transaction subject lists submitted by cooperating financial institutions, and historical compliance data accumulated by internal risk control. Update frequencies vary by source: regulatory lists are typically synchronized monthly or quarterly, while suspicious lists submitted by cooperating institutions can be synchronized in real time. Most documents use structured tables as their primary format, containing fields such as name, alias, nationality, document type and number, affiliated institutions, sanction reasons, and effective date. Most fields are identity-related, with no complex nested units.

Constraints on document parsing and chunking

The multi-source nature of data sources requires parsing logic to support submission files in different formats. Regulatory published lists are mostly standard tables with fixed column widths, while files submitted by cooperating institutions may have custom column order or merged cells. The presence of multiple fields and aliases requires retention of complete associated entity information during chunking, avoiding splitting the name, ID number, and alias of the same subject into different chunks. Real-time updated data sources require parsing processes to have high timeliness, preventing delays in risk control links caused by parsing delays. The field uniqueness requirement of structured tables requires parsing results to accurately map columns and values from the original document, preventing verification errors caused by misplaced fields.

Configuration settings

Configuration Item	Recommended Setting	Rationale
`PARSE_TABLE_STRUCTURE`	Force recognition of multi-column merged cells	Sanctions list documents often have multi-column alignment and alias merged cells, ensuring complete field mapping for each entity
`CHUNK_MAX_SIZE`	800–1200 characters	Entity information for sanctions list screening includes multiple associated fields. Chunks that are too long will lose field associations, while chunks that are too short will split complete information of a single entity
`PARSE_FILE_TIMEOUT_SECONDS`	120 seconds	Large full list files take longer to parse, avoiding parsing interruptions caused by default timeout values
`ENABLE_DOC_ALIAS_PARSE`	Enabled	Sanctions list documents often include alias fields, requiring accurate recognition and association with the main entity to improve verification accuracy
`RECALL_CHUNK_COUNT`	Calibrated according to business scenarios	Associated information of each entity is scattered across a small number of chunks, requiring adjustment based on actual recall needs

The parameter values provided on this page are general recommendations used as a starting point for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require case-by-case analysis. Testing on local samples should be completed before finalizing settings.

Three common configuration mistakes

Symptom: Misplaced fields appear in parsed lists, with multiple columns of content mixed together. Cause: The multi-column recognition configuration for PARSE_TABLE_STRUCTURE is not enabled. The default parsing logic processes content as a single column, leading to misplaced columns for names, ID numbers, and affiliated institutions in the list.
Symptom: A 408 Request Timeout error is returned when batch parsing large list files. Cause: The PARSE_FILE_TIMEOUT_SECONDS parameter is not adjusted, and the default short timeout value is used, which cannot complete full data parsing.
Symptom: Aliases and main information of the same entity cannot be associated during knowledge base recall. Cause: CHUNK_MAX_SIZE is set too small, splitting the alias and ID number of the same entity into different chunks, leading to broken associations.

How to confirm correct configuration

Upload a test list file with multiple columns and merged cells. Confirm that parsed table fields correspond one-to-one with the original document.
Randomly select an entity entry. Check whether its associated alias, ID number, and sanction reason are included in the same or adjacent chunks.
Trigger a batch parsing task. Confirm that the parsing process does not experience timeout interruptions, and that no table parsing failure errors appear in logs.
Initiate a knowledge base recall test. Verify that all associated fields of the target entity can be correctly recalled.

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.