What the data for this category looks like
Refractory material research report data primarily comes from public industry association reports, technical documents from manufacturing enterprises, quality inspection reports from third-party testing institutions, and academic research literature. Update cycles fall into two categories: regular and irregular. Industry association research reports are updated and released quarterly. Enterprise technical documents are updated irregularly alongside new product development and production capacity adjustments. Testing reports are generated synchronously with product batch deliveries.
Document structures typically include modules such as product model, physical and chemical indicators, application scenarios, and production process parameters. Fields mostly use standardized professional identifiers. For example, refractoriness is marked as a temperature value, and bulk density is marked with a density unit. Minor differences exist in field ordering and naming across documents from different sources.
What constraints do these characteristics impose on the knowledge base retrieval and recall link
The specialized field characteristics of refractory material research reports impose multiple constraints on the retrieval and recall process. First, standardized physical and chemical parameters and product models require retrieval to support field-level precise matching, to avoid irrelevant results introduced by generalized semantic matching. Second, the coexistence of multiple update cycles requires the knowledge base to distinguish between full and incremental update strategies, to adapt to the update needs of regular industry research reports and irregular enterprise documents. Third, individual research reports are lengthy and parameters have cross-page associations. Sufficient context windows must be retained during segmented recall to avoid breaking parameter logic. Finally, parameters for refractory materials vary significantly across different application scenarios, requiring support for filtering recall results by scenario tags to improve retrieval targeting.
How to set the configurations
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
PARSE_SEGMENT_LENGTH | 800–1200 characters | Physical and chemical parameter paragraphs in refractory material research reports are lengthy. Too short a segment will break parameter associations, while too long a segment will exceed the context window. This range balances content completeness and retrieval efficiency |
RECALL_TOP_K | Top 8–12 results | Professional content in refractory materials is highly concentrated. Too many recall results will introduce irrelevant information, while too few will miss relevant parameter combinations. This range covers core related content |
SIMILARITY_THRESHOLD | 0.75–0.85 | Semantic similarity requirements for professional terms are high. A threshold that is too low will introduce irrelevant material parameters, while a threshold that is too high will filter out valid related content |
UPLOAD_INCREMENTAL_MODE | Configured by data source type | Industry association research reports are updated fully quarterly, while enterprise technical documents are updated incrementally with new product releases. Distinct update strategies are required to adapt to different update cycles |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Individual refractory material research reports are lengthy, and parsing time is longer than that of general documents. Insufficient default duration will cause parsing interruptions |
FIELD_MATCH_ENABLE | Enabled | Refractory material documents contain a large number of standardized fields such as product model and refractoriness. Field matching can greatly improve retrieval accuracy |
The parameter values provided on this page are all 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, and it is recommended to test on your own samples before finalizing settings.
Three common mistakes
- Phenomenon: The exported knowledge base dataset CSV file only contains the index field and no content field. Cause: The document content export switch was not enabled, and only index metadata was synchronized.
- Phenomenon: The page count keeps refreshing when importing documents into the knowledge base, and the target page cannot be selected. Cause: Document parsing timed out before completion, the front-end polling did not obtain the parsing completion status, or the document format contains non-standard pagination markers.
- Phenomenon: The status keeps spinning after uploading a knowledge base file in an offline environment, and normal operation resumes after connecting to the internet. Cause: The system needs to access external APIs to complete format verification or dependent parsing. Dependent resources cannot be pulled in an offline environment, causing parsing blocking.
How to confirm that the configuration is correct
- Upload a standard refractory material research report, check the parsed segmented content, and confirm that core parameter paragraphs are not excessively segmented.
- Enter professional search terms such as "high-alumina refractory material bulk density", and check whether the field matching degree and similarity threshold of the recall results meet expectations.
- Configure an incremental update task, and verify whether the update frequencies of different data sources trigger according to preset rules.
- Export the knowledge base dataset, and confirm that the content field has been properly generated and contains the core content of the document.
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.