What the data for this category looks like
Commercial property intelligent due diligence data sources mainly include lease contracts, fire acceptance reports, monthly operation ledgers, rental revenue statements, business district passenger flow analysis documents, and others. Update frequency varies by document type: lease contracts are updated once when signed, operation ledgers are updated monthly or quarterly, and fire reports are updated during annual inspections. Document structures are mostly mixed format, including plain text analysis paragraphs and nested tables. Fields include per-area efficiency, occupancy rate, shared area, tenant industry classification, and others. Some fields have specific units, such as square meters, yuan/month/㎡.
What constraints these characteristics impose on the document parsing and chunking link
Mixed-format document structures require the parsing link to support both plain text and structured table extraction, to avoid losing row and column association information within tables. Scenarios with long documents and extremely large row counts require the chunking link to avoid excessive splitting that breaks context, and avoid creating chunks that are too large to exceed subsequent processing limits. Business fields with specific units require the chunking link to retain the binding relationship between fields and their units, to avoid ambiguity in cross-chunk business logic. Data sources with different update frequencies require the parsing link to support incremental identification of updated content, to avoid re-parsing unchanged data.
How to set the configurations
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
parse_mode | Mixed document parsing + structured table extraction | Commercial property due diligence documents contain both plain text analysis and multi-format table data; this mode preserves row and column association relationships within tables |
chunk_size | 800–1200 characters | Commercial property data includes business fields with units such as per-area efficiency and occupancy rate; this range covers the complete operation data segment for a single tenant, avoiding context loss after splitting |
excel_parse_strategy | Split by business dimension | Excel data with 15,000 rows contains row-level data for multiple tenants and floors; splitting by tenant or floor avoids mixed data within chunks |
chunk_overlap | 100–150 characters | Business district analysis reports, which are long text types, require retaining context association between adjacent paragraphs to avoid cross-chunk logical breaks |
max_parsing_chunk_length | 1500 characters | Word documents with 100,000 Chinese characters contain continuous format analysis paragraphs; limiting the maximum chunk length avoids single chunks exceeding the context limits of vector models |
parse_timeout | 300 seconds | Parsing large documents takes a long time; this duration covers the complete multi-table extraction and chunking process |
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 individual analysis, and it is recommended to test against your own samples before finalizing.
Three common mistakes
- Phenomenon: Parsed Excel data chunks include cross-floor rental data, or a single chunk has far more rows than the preset value. Cause: The
excel_parse_strategyis not configured to split by business dimension; the default continuous row splitting causes mixed data. - Phenomenon: A 100,000-character Chinese Word document triggers a
408 Request Timeouterror during parsing. Cause: Theparse_timeoutparameter is not adjusted; the default timeout duration is insufficient to complete full parsing of long documents. - Phenomenon: Some tenant's per-area efficiency data fields are empty, or unit information is lost after chunking. Cause: The table structured extraction mode of
parse_modeis not enabled; the plain text parsing mode cannot recognize the association between fields and units within tables.
How to confirm the configuration is correct
- Upload a single Excel test file with more than 10,000 rows, check the parsed chunk list to confirm that data within chunks is grouped by tenant or floor.
- Upload a single Word test document with more than 50,000 Chinese characters, check if chunk lengths fall within the preset range, with no chunks exceeding the maximum limit.
- Check the parsing log to confirm that all fields and units within tables are fully extracted, with no missing or confused entries.
- Initiate a knowledge base recall test to confirm that input business questions can match the corresponding chunk data, with no matching failures caused by context breaks.
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.