Document Parsing and Chunking for Chemical Fiber Financial

What the data for this category looks like

Chemical fiber industry financial report data primarily comes from periodic report PDF and Word documents disclosed by domestic and overseas stock exchanges, plus operation briefs released by industry associations. Update schedules follow regulatory requirements: annual reports are disclosed by the end of April each year, and quarterly reports are disclosed within one month after the end of each quarter.

Document structures include standardized financial statements, segmented product capacity and production data, raw material cost explanations and other fields. Capacity and production units are ten thousand tons, while revenue and cost units are hundred million yuan. Segmented categories such as polyester and nylon will separately list production and sales content for their core products.

What constraints do these characteristics impose on document parsing and chunking?

The structured characteristics and update schedule of chemical fiber financial reports create multiple constraints for document parsing and chunking.

Standardized financial statements and segmented product production and sales tables make up a large share of documents. Multiple unit fields are nested within tables, so accurate distinction between header rows and data rows is needed to avoid unit identification errors. Some documents have image-based tables that cannot extract text directly, requiring an additional OCR process.

There are significant format differences among batch-imported financial report documents. Chunking must retain contextual association for the same product’s production and sales data to avoid splitting critical information. Additionally, financial report disclosure cycles are concentrated, so performance requirements for high-frequency batch parsing must be met.

How to set the configurations

Configuration Item	Recommended Value	Rationale
`parse_table_enable`	Enabled	Chemical fiber financial reports contain large numbers of structured financial and production and sales tables. Enabling this option allows complete extraction of text content within tables
`parse_ocr_image_table`	Enabled	Some financial report documents have image-based tables. OCR processing is required to extract text that cannot be directly recognized
`chunk_max_size`	800–1200 characters	The length of single chemical fiber financial report documents varies widely. This range balances contextual association and chunking retrieval efficiency
`chunk_overlap_rate`	10–15%	Contextual association for segmented product production and sales data must be retained to avoid splitting core business information
`batch_parse_max_count`	50 per batch	Financial report disclosure cycles are concentrated. Batch parsing must control server load per batch
`parse_timeout`	300 seconds	Long documents include multiple tables and OCR processing steps, so sufficient time is needed to complete full parsing

The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material form, data volume and business rules. Specific issues require case-by-case analysis. It is recommended to test on your own samples before finalizing settings.

Three common errors

Issue: Missing text or misaligned fields in parsed image-based tables after import. Cause: The parse_ocr_image_table configuration is not enabled. Native text extraction alone cannot recognize table content embedded in images.
Issue: Production and sales data for the same segmented product is split into multiple independent chunks after chunking. Cause: The chunk_overlap_rate is set below the recommended range. Insufficient contextual association information is retained, leading to splitting of core business data.
Issue: 504 Gateway Timeout error returned during batch parsing. Cause: The parse_timeout setting is shorter than actual parsing time. Long documents with multiple tables and OCR processing steps exceed the configured threshold.

How to confirm the configuration is correct

Upload a single chemical fiber financial report document containing image-based tables. Check the integrity of table text in the parsing results to confirm whether the parse_ocr_image_table configuration is enabled as expected.
Import a long document containing segmented product production and sales data. Verify that associated information for the same product in the chunking results is not split. Adjust chunk_overlap_rate to a range suitable for your business.
Batch import multiple financial report documents. Monitor parsing task duration and server load. Adjust batch_parse_max_count and parse_timeout to values that match your current operating environment.
View detailed parsing task logs. Confirm that logs related to table parsing and OCR processing are generated normally, to verify that core configuration items are loaded correctly.

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.