What this category of data looks like
Crop farming investment research data covers multiple types of official public documents and first-hand survey materials. Sources include variety approval announcements, regional planting zoning documents, ten-day interval meteorological observation data, variety characteristic descriptions from seed enterprises, and first-hand records from field trials. Update rhythms vary significantly: variety approval announcements update with annual approval batches, meteorological data updates daily, and field trial reports release irregularly based on project progress. Document structures include structured tables (such as crop growth period and mu yield parameters) and unstructured long text (such as trial process descriptions). Core fields include crop type, planting region, growth cycle, and yield indicators. Common units are kilograms/mu, tons/hectare, degrees Celsius, and millimeters.
Constraints Imposed on Traceability
The mixed structure and varied update rhythms of crop farming data create multiple constraints for the traceability process. Coexisting structured and unstructured documents require distinct marking rules for field-level traceability and paragraph-level traceability, to avoid mixing up sources of different data types. Frequently updated meteorological data and irregularly updated trial reports require incremental update-based traceability version management to ensure the timeliness of cited content. Different sources of the same type of indicator (such as mu yield from different production regions) have variations, so scene annotations of the original source must be retained during traceability to prevent misuse of cross-region data.
Configuration Settings
| Configuration Item | Recommended Value | Rationale |
|---|---|---|
recall_top_k | Top 8-12 entries | Crop farming investment research data covers multiple production regions and multi-dimensional indicators, requiring sufficient candidate sources to be recalled to support accurate traceability |
chunk_size | 800-1200 characters | Crop farming documents include long sections of field trial records and structured parameter tables. This segment length preserves the integrity of professional semantics |
source_metadata_fields | Extract source_name, publish_date, crop_type, region, file_name | Matches the multi-dimensional traceability requirements of crop farming data, clearly annotating source type, release time, applicable crop and region |
rag_citation_score_threshold | 0.72-0.80 | Crop farming data has a high density of professional terms, requiring a raised threshold to filter low-relevance recall results and avoid invalid citations |
max_citation_per_response | 3-5 entries | Controls the number of citations per round of replies to avoid information overload, while covering core data sources |
enable_incremental_update | Enabled | Meteorological data and phenology data require frequent incremental updates to ensure the timeliness of cited content |
The parameter values provided on this page are common starting points for configuration. Actual values are affected by material format, data volume and business rules. Specific issues require targeted analysis. It is recommended to test against your own samples before finalizing settings.
Three Common Misconfigurations
- Phenomenon: The citations returned in a single round of replies are not the top-ranked results in the knowledge base. Cause: Semantic reranking rules are configured, which prioritize matching the semantic relevance of the query, do not reference the upload order or preset weights of original documents, and do not adjust the recall sorting logic.
- Phenomenon: The returned API call results do not include the file name information of citations. Cause: The
file_namefield is not configured for extraction insource_metadata_fields, or the related switch is not enabled, so traceability metadata is not included in the returned content. - Phenomenon: Rationality verification of cited content cannot be implemented in the workflow. Cause: The
enable_citation_verifyparameter is not bound, and verification rules are not configured for the professional attributes of crop farming data, so the large model cannot trigger compliance checks on cited content.
How to Confirm Configuration Is Effective
- Upload a crop farming field trial report and a meteorological data document. After triggering knowledge base parsing, check the metadata fields in the parsing details to confirm that
source_name,publish_date,file_nameand other fields have been correctly extracted. - Submit a query that includes specific crop production region and yield indicators. Check the citation list in the reply to confirm that the number of returned citations matches the configured value of
max_citation_per_response. - Call the API to submit a query. Check whether the
citationsfield in the returned results includes traceability-related fields such asfile_nameandscoreto confirm that the configuration takes effect. - After configuring the citation verification workflow, upload a document with conflicting data. After triggering a query, check the workflow logs to confirm that the verification logic has been triggered and relevant prompts are 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.