Data Profile for This Category
Data sources for chemical fiber industry due diligence reports include publicly monitored data from the China Chemical Fiber Industry Association, real-time quotes from commodity trading platforms, public customs declaration data from the General Administration of Customs, and public business reports from enterprises.
Data update frequencies vary:
- Spot quote data is updated daily
- Industry association monthly statistics are updated monthly
- Customs import and export data lags by 1 to 2 months
- Annual enterprise business reports are updated quarterly
Each individual due diligence report contains structured tables and qualitative analysis paragraphs. Table fields include product category, spot quote, production capacity, inventory level, and import and export scale, with corresponding units of yuan/ton, ten thousand tons/year, ten thousand tons, and ten thousand tons respectively. Paragraph content focuses on industry supply and demand changes and policy impacts.
Constraints Imposed on Vector Models and Indexing
Differences in data source update rhythms require the indexing system to support flexible switching between incremental and full indexing, to avoid repeated processing of already indexed historical data.
The high proportion of structured tables in document structures requires vector models to adapt to the encoding logic of structured fields. Otherwise, association information between product categories and corresponding quotes, production capacity will be lost.
Unified field formats across multiple data sources require standardized cleaning during the pre-indexing stage, such as unifying the expression of quote units.
The characteristic that individual documents contain multiple types of content requires reasonable chunking rules to avoid long text exceeding the context window limits of vector models.
The large number of sub-categories within the chemical fiber category requires vector indexes to support recall grouped by category, to improve retrieval accuracy.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
structured_data_parse_enable | Enabled | Chemical fiber due diligence reports contain a large number of structured tables. Enabling this setting extracts field association information, improving the accuracy of vector encoding |
chunk_size | 800–1200 characters | Adapts to the chunking needs of individual documents, avoids long text exceeding the context window of embedding models, while retaining the integrity of field associations |
similarity_threshold | 0.75–0.85 | Filters low-similarity results, avoids false matches with abnormally high similarity, and adapts to retrieval needs for the large number of chemical fiber sub-categories |
recall_top_k | Top 10–15 results | Covers retrieval needs across multiple categories, avoids missing due diligence data for relevant categories due to too few recalled entries |
index_refresh_interval | Daily/Weekly | Matches the update rhythms of different data sources. Refresh spot quote data daily, and refresh industry statistical data weekly |
embedding_batch_size | 32–64 | Balances indexing construction efficiency and memory usage, adapting to the needs of batch processing chemical fiber documents |
The parameter values provided on this page are common recommended starting points for determining configuration baselines. Actual values are affected by material format, data volume, and business rules. Specific issues require targeted analysis, and it is recommended to test on your own samples before finalizing settings.
Three Common Configuration Errors
- Symptom: Vector retrieval returns similarity scores outside a reasonable range, such as over 10000. Cause: The
similarity_thresholdparameter is not configured, or the threshold setting does not cover the filtering needs for abnormal matches. - Symptom: After uploading documents to the knowledge base, indexing progress stalls or shows as incomplete, and no matching results are returned by retrieval. Cause: The available channel for the embedding model is not correctly configured, causing embedding tasks to fail to trigger normally, and preventing document vectors from being generated.
- Symptom: A large number of irrelevant category data appears in retrieval results, and quote and production capacity information for core products is not recalled first. Cause: The
structured_data_parse_enableconfiguration is not enabled, and field association information in tables is not extracted, causing vector encoding to lose key associations from structured data.
How to Verify Correct Configuration
- Upload one chemical fiber due diligence report containing structured tables, view the parsed document content, and confirm that structured fields and their corresponding associated information have been correctly extracted.
- Run a retrieval test, enter a query term containing a specific chemical fiber category, and adjust the values of the
similarity_thresholdandrecall_top_kparameters according to business needs. - Manually trigger an index refresh operation, wait for the configured refresh cycle to end, and confirm that newly added data from data sources has been synchronized to the index library.
- View the running logs of the embedding model, and confirm that there are no error messages for channel exceptions or batch processing failures.
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.