What the data for this category looks like
Data sources cover property project operation ledgers, equipment maintenance records, industry policy documents, bidding project materials, and more. Update frequency fluctuates with business cycles: daily operation data is updated weekly, while policy documents are updated alongside new regulatory releases. Document types include structured Excel ledgers, Word maintenance plans, and PDF policy announcements. Fields include building area, collection amount, maintenance cycle, and others, with matching physical units and unified statistical standards. Some documents have fixed chapter hierarchies and repeated header and footer content.
What constraints do these characteristics impose on the document parsing and chunking workflow?
First, structured Excel ledgers contain multiple fine-grained columns. Chunking must avoid cross-field splicing to prevent semantic fragmentation. Second, Word documents for equipment maintenance files have fixed chapter hierarchies. Parsing must preserve the correspondence between headings and body content to avoid disordered hierarchy. Third, most industry policy PDFs use long paragraphs without line breaks. These must be split by legal clauses or logical paragraphs to avoid truncating complete policy statements. Fourth, scattered bidding project materials have repeated headers and footers across pages. Parsing must automatically remove redundant duplicate content to reduce invalid chunks.
How to set configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
segment_length | 800–1200 characters | Property management documents include structured ledgers and long-paragraph policy texts. This range balances semantic completeness and chunk retrieval efficiency |
custom_chunking_rule | Trigger by heading hierarchy + natural paragraph | Property documents have fixed chapter structures; splitting by headings preserves business logic hierarchy |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Parsing large annual operation ledgers or bidding materials takes significant time; this duration covers standard large-file parsing needs |
force_structured_parsing | Enable Excel/CSV format parsing | Property ledgers mostly have multi-field structured data; forced parsing preserves field correspondence and avoids out-of-order splicing |
chunk_overlap_length | 100–150 characters | Long-text chunking requires retaining contextual coherence to prevent semantic breaks that impair retrieval matching |
UPLOAD_FILE_MAX_SIZE | 500 MB | Meets the upload requirements for large project archives, covering file size limits for most property management scenarios |
The parameter values provided on this page are common starting points for configuration setup. Actual values are affected by material format, data volume, and business rules. Specific issues require individual analysis. It is recommended to test on self-provided samples before finalizing settings.
Three common mistakes
- Symptom: After uploading an Excel property fee ledger, retrieval results display garbled content spliced across fields. Cause:
force_structured_parsingwas not enabled, so parsing failed to preserve field correspondence, mixing data from different columns. - Symptom: After uploading a PDF industry policy document, knowledge base search tests return errors or no matching results. Cause:
segment_lengthwas set too large, causing complete policy clauses to be truncated and preventing the formation of valid retrieval chunks. - Symptom: After uploading a Word document containing equipment inspection photos, the large language model output does not include business descriptions associated with the images. Cause: OCR image parsing configuration was not enabled, so inspection text within images was not extracted as valid chunk content.
How to confirm configurations are correct
- Upload a single typical property management document, view the parsed chunk preview, and confirm that chunks retain the correspondence between chapter headings and body content.
- Run a knowledge base search test, enter keywords related to property management business, and confirm that returned chunk content matches business logic with no cross-field confusion.
- Upload a document containing tables and images, confirm that structured table fields are correctly retained and text within images has been extracted to generate chunks.
- Upload a document larger than standard size, confirm that the parsing task does not time out and chunk results fully cover the document content.
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.