What This Category of Data Looks Like
Pre-existing condition determination data primarily comes from pre-existing condition notification forms submitted by claim applicants, hospital outpatient and inpatient medical records, medical insurance settlement documents, and past underwriting records. Data is updated in real time for each individual claim application. Individual documents may contain mixed structured tables and unstructured text. Fields include diagnosed condition name, ICD-10 code, diagnosis time, treating hospital, treatment cost, and others. Time fields use the YYYY-MM-DD format, and costs are denominated in Chinese Yuan.
What Constraints These Characteristics Impose on Document Parsing and Chunking
Mixed structured and unstructured document structures require parsing tools to support both table extraction and free text extraction, to avoid missing structured condition list information. The numerous standardized fields require that chunking preserves relational connections between fields, and that text paragraphs spanning multiple fields are not arbitrarily split. The real-time update requirement means the parsing workflow cannot include overly long preprocessing steps, and must adapt to the rapid claim submission scenario. Diverse document sources require parsing tools to be compatible with different layout formats of PDF, Word, PPT and other files, to avoid parsing failures due to format differences.
How to Set the Configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Pre-existing condition-related documents often contain long medical records, and standard timeout durations are insufficient to complete full parsing |
CHUNK_SIZE | 800–1200 characters | Pre-existing condition determination requires retaining the relational information between conditions, diagnosis time, hospital and other details; chunk length is adapted to this relational requirement |
CHUNK_OVERLAP | 150–200 characters | Preserve contextual connections between chunks for conditions, to avoid losing critical information chains after splitting |
ENABLE_TABLE_EXTRACTION | Enabled | Pre-existing condition determination documents often contain structured notification tables; extracting tables can fully preserve the corresponding relationships between fields |
ENCODING_AUTO_DETECT | Enabled | Adapt to the encoding formats of documents from multiple sources, to avoid parsing errors caused by fixed encoding |
MAX_PARSE_FILE_SIZE | 50 MB | Cover the common maximum file size limit when a single claim application includes multiple attachments |
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 specific analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Mistakes
- The symptom is an error message "the argument ‘windows-1252’ is invalid encoding" returned during document parsing. The cause is that
ENCODING_AUTO_DETECTis not enabled, and forced use of a fixed encoding cannot be compatible with uploaded files using non-standard encodings. - The symptom is that the parsed chunk results lose the relational information between ICD-10 codes and their corresponding conditions. The cause is that
CHUNK_SIZEis set too small, splitting text lines that contain complete relational information into different chunks. - The symptom is an empty result returned after calling the document parsing tool in the workflow. The cause is that the
CUSTOM_READ_FILE_URLenvironment variable is not configured, making it impossible to read local files uploaded by the workflow.
How to Confirm the Configuration Is Correct
- Upload a pre-existing condition notification form that contains both structured tables and unstructured text, check the integrity of table extraction in the parsing results, and confirm that the configuration is effective.
- Check the encoding detection records in the parsing logs, and confirm that the automatic encoding detection function correctly identifies the encoding format of the uploaded document.
- Add a document parsing node to the workflow, upload a test file and trigger execution, and confirm that the returned chunk results contain complete relational fields such as conditions and diagnosis time.
- Adjust the
CHUNK_SIZEparameter, re-parse the same test document, compare the field integrity of the chunk results, and confirm that the configuration can take effect.
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.