Citation Source and Traceability for Textile Manufacturing

What Data for This Category Looks Like

Publicly traded companies in the textile manufacturing industry disclose financial report data primarily through periodic reports filed with the Shanghai and Shenzhen Stock Exchanges, as well as industry operation data released by the China National Textile and Apparel Council. Disclosure schedules follow fixed timelines: annual reports are released before April each year, semi-annual reports before August each year, and quarterly reports within one month after the end of each quarter. Most documents are in PDF format, containing structured tables and text passages. Core fields include operating revenue, operating costs, ending inventory balance, spinning capacity, fabric output, and others. Units include RMB 10,000 yuan, 10,000 meters, 10,000 spindles, and similar units. No industry-specific metrics beyond standard financial report fields require separate labeling.

Constraints Imposed by These Characteristics on Citation Source and Traceability

Structured tables and scattered fields in financial reports require precise matching of specific page numbers and table locations during traceability. Without this, referenced content cannot be accurately located. Fixed disclosure schedules require knowledge base synchronization nodes to align with disclosure cycles. This prevents referencing outdated data. Industry-specific capacity and output fields have no universal mapping rules. Custom association logic must be implemented, otherwise corresponding sources cannot be retrieved. PDF disclosure files may have split or misaligned tables. This causes annotation positions during traceability to shift from actual content, increasing verification difficulty.

Configuration Settings

Configuration Item	Recommended Value	Rationale
`PARSE_PDF_TABLE_MODE`	Precise table parsing mode	Textile manufacturing financial reports contain large numbers of structured capacity and financial tables. Precise mode preserves complete row and column structures, making it easier to trace and locate specific content
`RECALL_CHUNK_SIZE`	800–1200 characters	Core indicator passages in textile manufacturing financial reports are mostly 300–800 characters. This range covers complete context and avoids truncating critical information
`RECALL_TOP_K`	Top 3–5 results	Core data in textile manufacturing financial reports is scattered across a small number of sections. Too many retrieved results introduce irrelevant content and reduce response accuracy
`SOURCE_DISPLAY_FORMAT`	Display file name + page number + table ID	Structured tables in textile manufacturing financial reports require clear position labeling to help users verify data sources
`SYNC_CRON_EXPRESSION`	0 0 2 1,4,7,10 *	Aligns with the disclosure schedule of quarterly, semi-annual, and annual reports, ensuring knowledge base data is synchronized with the latest financial reports
`SIMILARITY_THRESHOLD`	0.75–0.85	Industry terminology for textile manufacturing is highly specialized. A higher threshold filters semantically similar but non-target content and improves retrieval accuracy

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. Each scenario requires individual analysis. It is recommended to test with your own samples before finalizing settings.

Three Common Misconfigurations

Issue: After enabling the citation reference feature, returned results do not display sources, or source fields are empty. Cause: The global ENABLE_SOURCE_REFERENCE switch is not enabled, or the SOURCE_DISPLAY_FORMAT parameter format is not configured correctly.
Issue: When calling a workflow via the Python API, the target knowledge base cannot be associated, and financial report data cannot be referenced. Cause: The knowledge base ID is not bound to the workflow input node, or the knowledge_base_id field is not included in the API request parameters.
Issue: Retrieved results include non-textile manufacturing financial report content that does not match the specialized knowledge base. Cause: The SIMILARITY_THRESHOLD value is set too low, resulting in retrieval of semantically similar but non-target category financial report data.

How to Verify Successful Configuration

Upload a single PDF of a publicly traded textile manufacturing company's financial report. After parsing is complete, view the preview page to confirm that table structures are intact and fields are not misaligned.
Submit a targeted test query such as "What was Company XX's spinning capacity in 2023". Check whether the returned result includes traceability information such as file name, page number, and table location.
Review the workflow input node configuration to confirm that the target knowledge base ID is bound, and that the API request parameters include the correct knowledge_base_id field.
Adjust SIMILARITY_THRESHOLD to the preset range, then repeat the same query. Compare changes in the relevance of retrieved results to confirm that the parameter takes effect.

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.