What the Data for This Category Looks Like
The data for this category comes from real estate registration information systems, cadastral survey databases, housing transaction online signing systems, tax systems, and electronic certificate repositories, with a daily update frequency. Commonly processed documents include registration applications, ownership certificates, survey results, tax payment vouchers, real estate ownership certificates, and registration books. These include both paragraph-style application descriptions and structured tabular data. Fields cover rights subjects, location addresses, right types, and other items. It is necessary to adapt to multi-source heterogeneous business data, with no unified fixed format.
Constraints on Document Parsing and Chunking
The multi-source heterogeneous data, diverse document formats, and high-frequency update nature of real estate registration business impose multiple constraints on document parsing and chunking. First, individual business documents are exported across multiple systems, leading to inconsistent fields and mixed formats. Parsing tools must adapt to different document types. Second, a single registration application material can reach 100,000 Chinese characters, or contain 15,000 rows of structured tax data. This places requirements on file upload, parsing timeout limits, and chunking thresholds. Finally, business data requires accurate association between ownership sources and survey information. Chunking must avoid splitting cross-document associated content to ensure the accuracy of subsequent inquiry responses.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Adapts to the field length of real estate registration documents and the context limits of mainstream vector models, avoiding vectorization errors caused by excessive content in a single chunk |
chunkSplitter | Split by paragraph + fixed characters | Balances parsing integrity for both paragraph-style application descriptions and structured tabular data, avoiding splitting ownership-related content |
UPLOAD_FILE_MAX_SIZE | 2000 MB | Supports uploading Word documents with 100,000 Chinese characters or Excel data with 15,000 rows, covering the size range of most real estate registration business materials |
PARSE_FILE_TIMEOUT_SECONDS | 600 seconds | Matches the time required for large file parsing, preventing chunking tasks from being interrupted due to timeout |
chunkSettingMode | Custom mode | Allows adjustment of chunking rules for multi-source heterogeneous data in real estate registration, adapting to format differences across different business documents |
Three Common Mistakes
- Phenomenon: After uploading a Word document with 100,000 characters or Excel data with 15,000 rows, some empty chunks appear in the chunk list, or the vectorization task reports a "vector generation failed" error. Cause: The
UPLOAD_FILE_MAX_SIZEorPARSE_FILE_TIMEOUT_SECONDSparameters are not adjusted, leading to large file parsing timeout or incomplete chunking. Retrying multiple times only provides temporary recovery and cannot resolve the issue permanently. - Phenomenon: After importing real estate registration JSON data queried from a database into a knowledge base, some fields (such as right type, location address) are missing. Cause: Custom field mapping for document parsing is not configured, and the heterogeneous JSON format exported from multiple systems is not adapted, leading to omission of key business fields during parsing.
- Phenomenon: Duplicate ownership description fragments appear after chunking, or cross-page survey data is split. Cause: Chunk overlap function is not enabled, or
chunkSplitteris only set to fixed character splitting without combining paragraph boundaries for chunking, leading to forced splitting of business-related content.
How to Confirm Proper Configuration
- Upload a single real estate registration application document with 100,000 characters, and check that the character count of each chunk in the chunk list falls within the 800–1200 character range.
- Upload an Excel tax payment voucher with 15,000 rows, and verify that the parsed data fields completely match the original table, with no missing or misaligned fields.
- Run a workflow that includes large file parsing, and check the FastGPT v4.17.0 system logs for no timeout errors corresponding to
PARSE_FILE_TIMEOUT_SECONDS. - Trigger a chunk vectorization task, confirm there are no duplicate errors, then conduct multiple rounds of inquiry tests to verify the accuracy of responses related to ownership information.
The values provided here are common starting points and should be evaluated against the reader's own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.