What this category of data looks like
Railway and highway financial report and operation data mainly comes from listed companies’ periodic reports, public statistical bulletins issued by transportation authorities, and enterprise operation disclosure announcements. Data update cadence follows quarterly and annual periodic financial report disclosures, plus monthly operation data updates. Document structure includes core sections such as operation scale, passenger and freight volume, revenue and costs, and assets and liabilities. Fields include passenger throughput, freight throughput, operation mileage, and toll revenue, with corresponding units of 10,000 persons, 10,000 tons, kilometers, and 10,000 yuan. Most data is stored as structured PDF documents, with some content from public web statistical sources.
What constraints do these characteristics impose on the knowledge base retrieval and recall link
Data sources are dispersed, covering corporate periodic reports and industry authority statistical content. This requires retrieval systems to support cross-source recall, preventing results from being limited to a single channel. Update cadence is fixed and relatively frequent, including monthly operation data and quarterly/annual financial reports. This requires the system to support periodic incremental synchronization to reduce resource consumption from full-scale processing. Documents are a mix of structured tables and unstructured text. The binding relationship between fields and units must be preserved to avoid losing data precision during retrieval. Core indicators differ between railway and highway categories. Retrieval must filter irrelevant entries by category to improve recall accuracy.
How to configure the system
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
recall_count | Top 10 | Single railway and highway financial report documents have large data volumes. Sufficient recall entries are needed to cover core indicators and related content |
similarity_threshold | 0.75–0.85 | Financial report data has high precision requirements. Low-similarity noise content must be filtered to avoid irrelevant entries interfering with analysis |
chunk_size | 800–1200 characters | Financial reports mix tables and text. Segments that are too long will lose the association between fields and units, while segments that are too short will destroy indicator integrity |
PARSE_TABLE_STRICT | Enabled | Structured tables in financial reports are core data sources. Strict parsing can fully retain the corresponding relationship between fields, values, and units |
increment_sync_cron | 0 0 2 * * * | Perform incremental synchronization at 2:00 AM daily, matching the regular disclosure cadence of monthly operation data |
UPLOAD_FILE_MAX_SIZE | 1000 MB | Single annual financial report PDF files usually do not exceed this threshold, adapting to large document upload requirements |
The parameter values provided on this page are common starting points for configuration. Actual values are influenced by material form, data volume, and business rules. Each scenario requires tailored analysis. It is recommended to test on your own samples before finalizing settings.
Three common errors
- Phenomenon: Retrieval results do not include high-match entries ranked highly in the knowledge base. Cause: No reasonable
similarity_thresholdinterval is configured, orrecall_countis set too low, resulting in high-similarity entries being filtered out or not recalled. - Phenomenon: Generated analysis content references fields that do not match the units in the document. Cause: The
PARSE_TABLE_STRICTconfiguration is not enabled. Table parsing loses the binding relationship between fields and units, leading to impaired data precision. - Phenomenon: Incrementally synchronized financial report data is not updated as planned. Cause: The cycle of the
increment_sync_cronconfiguration does not match the industry data disclosure cadence, or no file filtering rules are configured, resulting in repeated uploads of old files without triggering updates.
How to confirm configuration is complete
- Upload a single railway or highway financial report document, view the parsed text and table content, confirm that fields and units are fully retained, and verify that the
PARSE_TABLE_STRICTconfiguration is active. - Trigger a manual incremental synchronization, check the number of updated files and timestamps in the synchronization log, and confirm that the
increment_sync_cronconfiguration triggers as expected. - Enter specific financial report indicator keywords to initiate retrieval, view the sorted recall entries and similarity scores, and confirm that the
similarity_thresholdandrecall_countconfigurations meet requirements. - Test retrieval of both corporate financial reports and industry statistical data, confirm that cross-source recall configuration is active, and that returned entries cover financial content from different sources.
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.