Knowledge Base Retrieval and Recall for Minor Metals Investment Research Knowledge Base Construction

Minor metals investment research data primarily comes from public industry association reports, customs import and export statistics, spot trading

What Data for This Category Looks Like

Minor metals investment research data primarily comes from public industry association reports, customs import and export statistics, spot trading platform quotes, publicly disclosed documents from mining enterprises, and research reports from professional investment research institutions. Update cycles include daily spot quotes, weekly supply and demand tracking, monthly industry updates, and irregular special research reports. Document types include structured market tables, unstructured research report documents, and policy files. Structured table fields include product name, specification model, origin, quote, and price change range. Common units are yuan/ton, yuan/kilogram, or metal content percentage.

The multi-type, multi-update cycle, and multi-field unit characteristics of minor metals data impose multiple constraints on the retrieval and recall process. Structured market tables require precise field matching, otherwise irrelevant unstructured research report content will be included. High-frequency updated spot data requires an incremental synchronization mechanism to avoid resource waste and data lag caused by full synchronization. When splitting long research report documents, context association must be retained to prevent semantic fragmentation after splitting that reduces retrieval relevance. Quote data with different units must be normalized before recall, otherwise quotes for the same product with different specifications cannot be matched correctly.

Configuration Settings

Configuration ItemRecommended ValueRationale for This Setting
CHUNK_SIZE800–1200 charactersMinor metals research reports mostly contain long paragraphs of supply and demand analysis. This length retains context association and avoids semantic fragmentation after splitting
RECALL_TOP_KTop 10 resultsMinor metals have few product varieties but many detailed specifications. A sufficient number of candidate results must be recalled to cover market data for different specifications
SIMILARITY_THRESHOLD0.75–0.85Avoid low-relevance unstructured documents while retaining matching results for detailed specifications
PARSE_FILE_MAX_SIZE50 MBSingle industry research reports or supply and demand reports usually do not exceed this size, to avoid parsing timeouts
UPLOAD_INCREMENTAL_INTERVAL3600 secondsSpot quotes are updated daily. Hourly incremental synchronization ensures data timeliness
IMAGE_PARSE_ENABLEEnabledSome market documents contain K-line charts and specification annotation images. Text information in images must be parsed

The parameter values provided on this page are conventional recommendations used to establish a starting point 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

  • Symptom: After uploading a document containing K-line charts, retrieval results do not extract text content from the image. Cause: The IMAGE_PARSE_ENABLE configuration item is not enabled, and only native text within the document is parsed.
  • Symptom: Quotes from the same product with different origins cannot be matched correctly in retrieval results. Cause: No normalization configuration is applied to units in structured tables, causing quotes in yuan/ton and yuan/kilogram to be judged as irrelevant content.
  • Symptom: Responses returned by the knowledge base application exceed preset word count limits. Cause: No limit is set on the total context length retrieved by the knowledge base, causing the recalled multiple segments to exceed the context threshold for subsequent large model processing.

How to Confirm Configuration Correctness

  • Upload a test document containing market tables and K-line charts, check if the parsed text includes annotation text from the image to confirm the configuration is effective.
  • Submit a query containing detailed minor metal specifications, verify that the number of recall results matches the preset recall count setting.
  • Check the knowledge base's incremental synchronization logs to confirm that the update frequency matches the configured synchronization interval.
  • Trigger a complete retrieval process, verify that the returned context content has no semantic fragmentation, confirming that the chunking configuration is reasonable.

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.