What data looks like for this category
Refractory material investment research data primarily comes from national standard documents, production enterprise quality inspection reports, kiln operation logs, raw material supplier quality inspection sheets, and industry association quarterly reports. The update rhythm varies significantly. Industry standards are updated every 2-3 years. Enterprise quality inspection reports are updated alongside production batches, and industry reports are released quarterly. Most document structures include standardized parameter fields, such as refractoriness, load softening temperature (unit: ℃), chemical composition proportion (unit: %), and kiln continuous operation duration (unit: hours). Some documents also include identifying information such as batch numbers and production plant locations.
Constraints on retrieval and recall from these data characteristics
The multi-source heterogeneous data characteristics of refractory materials impose multiple constraints on the retrieval and recall link. Document formats vary widely across different sources, so field standardization mapping must be completed first. Without this, parameter matching confusion occurs in recall results. Data with different update rhythms requires configuring incremental index trigger rules to avoid excessive computing resource usage from full reindexing. For parameter fields with clear physical units, if units are not associated during retrieval, semantic matching deviations occur. A unit standardization process must be added during the preprocessing stage. Additionally, identifying fields such as batch numbers and production plant locations must support filtering recall by attribute to meet traceability requirements for production batches in investment research scenarios. For long-text kiln operation logs, parameter context must be retained during segmentation to prevent key parameter information from being truncated.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
chunkSize | 800–1200 characters | Refractory material documents mostly contain continuous parameter descriptions. This range preserves the association between parameters and context, avoiding truncation of key information |
similarityThreshold | 0.72–0.85 | Parameter-based retrieval for refractory materials requires high matching accuracy. A value that is too low will introduce irrelevant results, while a value that is too high will miss valid matching items |
RECALL_TOP_K | Top 8–12 results | Investment research scenarios need to cover multi-source data of the same parameter type. Too many results will increase subsequent reranking pressure, while too few will not meet traceability requirements |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Large quality inspection reports or kiln log documents have lengthy content, so sufficient parsing time must be reserved |
ENABLE_FIELD_FILTER | Enabled | Refractory material data includes clear parameter fields. Enabling this allows precise filtering of recall results by attributes such as composition and temperature |
EMBEDDING_BATCH_SIZE | 32–64 | When batch processing multi-field data for refractory materials, this range balances memory usage and parsing speed |
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 case-by-case analysis, and testing against local samples prior to final configuration is advised.
Three Common Misconfigurations
- Dataset status in the interface remains "Indexing" with no progress updates. This occurs when incremental index trigger rules are not configured, and the retry mechanism is not triggered during parsing timeout when fully indexing large refractory material quality inspection reports.
- Abnormally high similarity values (such as 10000+) are returned after calling the embedding model. This occurs when unit standardization preprocessing is not enabled, and parameter units are not associated during retrieval, leading to deviations in embedding vector matching logic.
- No matching recall results are returned after uploading documents to the knowledge base, and no data is returned for field filtering. This occurs when the
ENABLE_FIELD_FILTERconfiguration is not enabled, or the mapped field name does not match the field name in the retrieval request.
How to Verify Proper Configuration
- Upload a single refractory material quality inspection report of approximately 1000 characters, view the segmented content after parsing, and confirm that parameters and context are not truncated.
- Initiate a retrieval request containing clear parameters such as "Al2O3 content ≥85%", and check whether the recall results include matching content for the corresponding fields.
- View the embedding task logs, confirm that the batch processing size falls within the configured
EMBEDDING_BATCH_SIZErange, and there are no out-of-memory error reports. - Test filtering recall by the "production batch" attribute, and confirm that only document content matching this identifier is returned.
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.