What This Category of Data Looks Like
Commercial real estate yield rate-related data primarily comes from real estate registration platforms, property operation ledgers, and regional business monitoring systems. Data update cycles are mostly monthly or quarterly. Some core commercial district projects have higher update frequencies for real-time signing and passenger flow data. Each data document includes fields such as project unique identifier, leased property area, total current collected rent, fixed operating costs, and total leasable area. Units include square meters, yuan per square meter per month, ten thousand yuan, and others. Some fields require cross-document verification linked to project filing numbers.
Constraints on Forms and Interactions
Because data sources are scattered and cross-system association is required, forms must support bulk import of multi-dimensional ledger data, and provide an entry for manual field completion. Differences in data update rhythms require forms to allow custom refresh cycles to adapt to different statistical dimensions such as monthly and quarterly. There are strong relationships between fields: for example, collected rent must be linked with leased area to calculate unit rent. Forms must include built-in field verification rules to avoid unit mismatches or numerical logic conflicts. Some projects require association with regional business monitoring data; the interaction link must support one-click pulling of external data to fill corresponding fields, reducing manual entry errors.
How to Configure Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
recall_count | Top 3-5 entries | Commercial real estate yield rate data has strong field correlations; too many recalled results will increase the form verification burden |
similarity_threshold | 0.75-0.85 | Match core fields such as project numbers and rent values, filter invalid data with low matching degrees |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Bulk imported commercial real estate ledger files contain data for multiple projects, with parsing time longer than general scenarios |
max_input_tokens | 8000-12000 characters | A single commercial real estate data document contains multi-dimensional associated fields, requiring space to hold complete imported content |
field_linkage_verification | Enable automatic verification | Commercial real estate fields have calculation correlations between rent and area, requiring built-in linkage verification rules |
workflow_run_timeout | 600 seconds | The process of pulling and verifying data across data sources takes a long time, so the overall runtime must be matched |
The parameter values provided on this page are conventional 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.
Three Common Mistakes
- A
Cannot convert undefined or null to objecterror pops up after workflow runs. The cause is that the form does not have required field interception rules configured. When core fields such as commercial real estate project parcel numbers and leased area are not filled in, the subsequent process is triggered directly, resulting in null value conversion errors during data parsing. - Only 1 matching data entry is returned after retrieval, making it impossible to obtain multi-dimensional associated content. The cause is that
recall_countis set to 1, which does not adapt to the scenario requirement that commercial real estate data requires multi-dimensional reference. - An input error occurs when referencing the created plugin in other workflows. The cause is that the form does not correctly map the commercial real estate-specific fields required by the plugin, and fields such as project filing number and current rent are not passed to the plugin node, resulting in incomplete parameters.
How to Confirm Configuration Is Complete
- Manually enter a complete set of commercial real estate project data, trigger the form verification process, and confirm that required field interception and linkage verification rules are triggered as expected.
- Import a ledger file that meets the format requirements, check whether the form automatically fills in corresponding fields, and confirm that the data parsing logic is normal.
- Run a workflow that includes field verification, confirm that no null value conversion errors occur, and confirm that the null value interception configuration is effective.
- Reference the configured plugin in a workflow, pass in commercial real estate-specific fields, check whether the plugin node normally receives parameters, and confirm that the mapping relationship is correct.
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.