Context and Token for Carbon Steel Investment Research Knowledge Base Construction

Carbon steel data primarily comes from public commodity exchange market data, monthly steel industry association reports, steel plant production and

What this category's data looks like

Carbon steel data primarily comes from public commodity exchange market data, monthly steel industry association reports, steel plant production and sales ledgers, and spot trader quotes. Update frequencies cover daily (spot prices, inventory data), monthly (industry supply and demand reports), quarterly (capacity statistics), and annual (industrial planning).

Documents include structured specification-price comparison tables, semi-structured supply and demand analysis texts, and policy documents. Fields include steel grade, nominal thickness/diameter, pricing unit yuan/ton, inventory unit 10,000 tons, and more. Some reports include additional fields such as regional price spreads and logistics costs.

Constraints on context and token handling

The high proportion of structured data, numerous fields, and detailed specification breakdowns in carbon steel data make standard chunking logic easily split associated information for the same steel grade. This damages context integrity. Daily high-frequency market data has a large volume. Token consumption per single document far exceeds that of standard industry texts, easily triggering token limit restrictions.

Subtle differences exist in field units and statistical standards across different documents. Failure to align these during context binding leads to information conflicts in recall results. Carbon steel investment research relies on precise category references. If token splitting does not preserve proper terminology integrity, matching accuracy for subsequent retrieval decreases.

Configuration settings

Configuration ItemRecommended ValueRationale
chunkSize800–1200 charactersAdapts to carbon steel document structures that mix structured tables and analysis texts. Balances single-chunk token consumption and information integrity
maxContextToken10000–14000 tokenCovers the typical context requirement of 3 trading days' market data plus 1 monthly supply and demand report in carbon steel investment research
recallCountTop 5–7 resultsBalances comparative analysis needs for mainstream steel grades. Avoids excessive redundant information occupying context tokens
chunkOverlap10–15 %Retains steel grade and pricing information across segments. Prevents splitting from breaking the association of same-specification data
similarityThreshold0.78–0.82Filters non-target grade carbon steel data. Improves retrieval matching accuracy

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 it is recommended to test against your own samples before finalizing.

Three common misconfigurations

  • Phenomenon: Carbon steel proper terminology such as HRB400 deformed steel bar, HPB300 wire rod entered into the knowledge base is split into multiple independent segments. Scattered single characters or short phrases appear in the fullTextTokens field. Cause: No keyword whitelist for forbidden chunking is configured. The default chunking logic breaks the integrity of proper terminology.
  • Phenomenon: When uploading a carbon steel monthly supply and demand report, the system returns a token limit exceeded error. Parsed document fragments may also be incomplete. Cause: The maxContextToken configuration is not adjusted. The low threshold setting for general product categories is used, which cannot cover the token consumption of long carbon steel documents.
  • Phenomenon: The same carbon steel price table appears as multiple discontinuous fragments in search results. This makes it impossible to view the complete daily price trend. Cause: The unit of chunkSize is incorrectly set to token instead of character. The chunking logic does not match the row width of carbon steel structured tables.

How to confirm proper configuration

  • View the parsed document fragment list. Confirm that carbon steel proper terminology is not split into scattered segments. Verify that the forbidden chunking configuration is active.
  • Upload a carbon steel document containing a complete price table. Check the parsed token consumption statistics. Confirm that the preset token limit is not triggered.
  • Initiate a search for a specific steel grade. Review the number of recall results and the matching logic of the similarity threshold. Ensure that recall results meet expectations.
  • View the fullTextTokens field in the dataset_datas table. Confirm that the token sequence of the target text block is complete. No abnormal splitting should appear.

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.