What the Data for This Category Looks Like
The data for cement research reports comes primarily from monthly operational monitoring reports from national building materials industry associations, public regular reports of listed building materials enterprises, and regional spot transaction data from commodity spot trading platforms. Updates follow a standard monthly cadence. Temporary special research reports are added when raw material prices fluctuate sharply or industrial capacity adjustment policies are issued.
The structure of a single research report usually includes overall industry operational overview, regional market supply and demand conditions, price and cost data for core product categories, upstream and downstream industrial correlation analysis, and policy trend interpretations. Fields included in the documents cover regional spot prices (unit: yuan/ton), capacity operation data, cost components, and policy document number references. Some research reports also include regional logistics and transportation data.
Constraints on Retrieval and Recall
The mixed multi-source data, uneven update cadence, long single-document length split by region or category, and presence of specific unit-based quantitative fields create multiple constraints for the retrieval and recall process.
Multi-source data includes both structured monitoring data and unstructured analytical text. A combination of structured metadata matching and semantic vector recall is required to avoid missing precise structured indicators when using a single recall method. Temporary special research reports require support for incremental embedding tasks to reduce resource overhead from full reprocessing.
Single research reports split content by region and category. When splitting into segments, the contextual association of regions and categories must be preserved to avoid recall fragments breaking complete information. For quantitative indicators with specific units, retrieval must match the semantics of both the indicator and its unit to improve recall accuracy.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunk_size | 800–1200 characters | Cement research reports are divided by region or category per single document. This segment length preserves complete analytical context for a single region or category, avoiding fragmented segments |
embedding_model | Multilingual general-purpose vector model | Covers simplified Chinese expressions commonly used in domestic research reports, adapts to multilingual recall optimization requirements, and resolves poor multilingual recall rates from earlier model versions |
batch_embed_max_size | 50 documents/batch | Balances single-batch processing efficiency and memory usage, adapting to scenario requirements for batch re-embedding of cement research reports |
recall_top_k | Top 10 results | Covers the information distribution across multiple regions and product categories in cement research reports, avoiding missing key regional data due to too few recall results |
similarity_threshold | 0.65–0.75 | Filters low-correlation recall results, adapting to precise matching requirements for segmented product categories and regional contexts in cement research reports |
split_mode | Paragraph-first | Follows the split mode added in version 4.9.10, preserves the original paragraph logic of research reports, and adapts to recall of structured content |
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 individual analysis. It is recommended to test on your own samples before finalizing settings.
Three Common Misconfigurations
- Issue: After running a batch re-embedding task, recall rates do not improve when searching for cement research reports in multilingual expressions. Cause: The embedding model was not switched to a multilingual-compatible model, and the initial single-language vector model configuration remains in use.
- Issue: When using the paragraph-first split mode from version 4.9.10, calling the create text collection interface returns a 400 parameter error. Cause: The
split_modefield was not passed in the interface request body with a value ofparagraph, or the field value format does not meet interface specifications. - Issue: After selecting cement research reports in Feishu Docs and adding them to the knowledge base, parsed content for the corresponding files does not appear in the knowledge base. Cause: Access permissions for the Feishu Docs were not granted to the bound robot account, or the documents are in an encrypted format that cannot be read.
How to Confirm Proper Configuration
- Run an embedding test for a single cement research report, check if the segmented text retains complete context for regions or categories, and confirm the segment configuration meets expectations.
- Launch a small-batch document re-embedding task, verify that the multilingual vector model's recall results cover simplified Chinese research report content, and confirm the embedding model configuration is correct.
- Call the retrieval interface, input a query term that includes regions and product categories, check the number of recall results and their similarity scores, and adjust recall parameters to a range that meets business requirements.
- Test uploading cement research report files via an external interface, confirm that the file parsing status updates to completed within a reasonable time frame, and verify that interface parameters and permission configurations are correct.
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.