What Data for This Category Looks Like
Iron ore investment research data primarily comes from public market data of the Dalian Commodity Exchange, loading ledgers from major domestic ports, public quotations from upstream and downstream enterprises in the steel industry chain, and regular research reports from industry research institutions. Data update frequencies vary by type: spot transaction prices and port inventory data are updated daily, futures market data is synchronized in real time, and industry research reports are released weekly or monthly. Most documents are structured tables paired with analytical paragraphs, containing fields such as region classification, product grade, transaction price, inventory scale, arrival cycle, and others. Units include yuan/ton, ten thousand tons, calendar days, and similar metrics.
What Constraints Do These Characteristics Impose on Multi-turn Dialogue and Prompt Engineering
The multi-source and time-sensitive nature of iron ore data requires clear differentiation of data type recall scopes during multi-turn dialogue, to avoid returning incorrect information across categories. The high proportion of structured documents requires prompts to guide the model to prioritize extracting precise fields from tables, rather than relying on vague analysis from unstructured text. The multi-field classification attribute requires multi-turn dialogue to gradually guide users to clarify limiting conditions such as region and product grade, to narrow the recall scope. Real-time updated market data requires associating the latest dataset synchronization tasks in the configuration, to avoid returning expired content.
How to Set the Configuration
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
recall_count | 8-12 results | Iron ore data has many fields and detailed classifications. Excessive recall will exceed the context window, while insufficient recall will miss valid data for key regions or grades |
similarity_threshold | 0.75-0.85 | Iron ore data has high precision requirements. A threshold that is too low will recall irrelevant product data, while a threshold that is too high will miss valid content for the same product category across different regions |
maxContext | 8000-12000 characters | Individual iron ore analysis reports are relatively long. Multi-turn dialogue needs to retain context information from multiple interactions to avoid truncation of key content |
PARSE_FILE_TIMEOUT_SECONDS | 300 seconds | Parsing iron ore documents that contain structured tables requires a long processing time, to avoid parsing failures for large-volume documents |
prompt_template | Prioritize extracting precise fields from tables. If the user does not specify a region or grade, actively ask for supplementary information | Adapt to the multi-field classification attribute of iron ore data. Clarifying limiting conditions is required to accurately recall target content |
reranked_return_count | 4-6 results | Multi-turn dialogue needs to prioritize displaying the most relevant structured data, to avoid information overload that affects the interaction experience |
The parameter values provided on this page are common recommended starting points for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require specific analysis, and it is recommended to test on your own samples before finalizing settings.
Three Common Mistakes to Avoid
- Returning a
404 status code (no body)during dialogue. The cause is incorrect configuration of the knowledge base API call permissions, or the associated dataset has not completed synchronous upload. - Being unable to specify a specific dataset for search via prompts. The cause is not clearly binding the unique identifier of the corresponding dataset in the prompt template, or not enabling the multi-dataset recall configuration switch.
- The dialogue opening not displaying preset multiple guiding questions. The cause is not configuring the preset question logic for the opening in
prompt_template, or not enabling the dialogue opening display switch.
How to Confirm the Configuration Is Correct
- Initiate a single-turn precise query to verify whether iron ore data for the corresponding region and grade can be recalled. If the recall scope is incorrect, adjust the value of the corresponding configuration item.
- Initiate multi-turn interaction to verify whether the model will actively ask for unspecified limiting parameters. If it does not actively ask, adjust the guiding logic of
prompt_template. - Upload a single large-volume structured iron ore document to verify whether a parsing timeout error is triggered. If an error is triggered, adjust the value of
PARSE_FILE_TIMEOUT_SECONDS. - Call the dialogue interface to verify whether the returned results include reference source fields. If they do not, enable the source display configuration item of the knowledge base.
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.