What This Category of Data Looks Like
This category of data is primarily sourced from highway maintenance management systems, bridge and tunnel monitoring systems, road patrol inspection systems, and traffic flow monitoring data. Daily documents include maintenance plans, patrol logs, defect disposal reports, road construction permits, road property damage compensation forms, and similar items. Document update frequency is daily. Some patrol logs and defect statistics documents are multi-row Excel tables, with fields including road section code, patrol period, defect type, disposal status, and others. There is no unified fixed cross-document field format.
Constraints Imposed on Knowledge Base Retrieval and Recall
Multi-source data is stored in scattered locations, so the retrieval link must support joint recall of cross-system datasets. Daily document updates require incremental indexing to run daily, to maintain data timeliness. Multi-row table documents require table structure parsing and field extraction prior to retrieval. This prevents text fragmentation from harming recall accuracy. High-frequency business scenarios focus on defect disposal, road construction, and road property compensation workflows. Retrieval must first match keywords and semantic meaning from documents related to these scenarios. It must also block non-business system data from retrieval results, to keep policy Q&A responses targeted.
Configuration Settings
| Configuration Item | Recommended Setting | Rationale |
|---|---|---|
similarity | 0.75–0.85 | Policy Q&A requires high confidence levels to filter low-relevance content and avoid misleading business decisions |
limit | Top 10 results | The total volume of policy documents for this category is manageable. Too many recalled results will increase context processing load |
searchMode | Semantic retrieval + keyword hybrid | Balances precise keyword matching and semantic association understanding for policy text |
usingReRank | Enabled | Improves ranking accuracy for long documents and multi-field documents, matching the complex structure of policy documents |
datasetSearchUsingExtensionQuery | Enabled | Expands synonymous expressions for policy terminology, covering question wording habits of different business personnel |
collectionIds | Bind to corresponding maintenance policy datasets | Isolates non-business related data, ensuring retrieval scope focuses on highway maintenance and road property rights management content |
Three Common Configuration Mistakes
- Phenomenon: Fields in imported Excel-format patrol logs are empty. Cause: Table parsing configuration is not enabled, and chunking rules for multi-row tables are not configured. This results in failed document parsing, with no valid retrieval content extracted.
- Phenomenon: Knowledge base search exceeds 30 seconds. Cause: The
limitparameter is not configured, leading to recall of too many irrelevant documents. This causes context processing timeout, and results cannot be returned promptly. - Phenomenon: The knowledge base never returns valid content. Cause:
collectionIdsis not bound to the corresponding maintenance policy dataset, or incremental indexing is not triggered daily. Business data is not synchronized to the retrieval database.
How to Verify Successful Configuration
- Upload a test road construction permit document, initiate a query containing "road construction requirements", and verify that the recalled results filtered by the
similaritythreshold include this document. - Initiate a query containing "pavement defect disposal", check that
usingReRankplaces defect disposal reports at the top of retrieval results. - View the incremental indexing logs in FastGPT v4.17.0, confirm that data synchronization completes daily at the set frequency.
- Upload an Excel-format patrol log, verify that fields such as road section code and defect type from the table are correctly extracted and included in the retrieval scope.
The values provided are common starting points, and should be evaluated against the reader’s own samples.
Question material comes from public community discussions. Configuration values are common starting points and should be measured against your own samples. Verified on 2026-09-28.