Knowledge Base Retrieval and Recall for Ordnance Equipment

What the data for this category looks like

This category’s data comes from several sources. These include National Military Standard (GJB) documents, equipment finalization technical reports, public defense industry research reports, equipment test monitoring data, and public information from the State Administration of Science, Technology and Industry for National Defense. Updates trigger on specific milestones. These milestones include new equipment project initiation and finalization. Bulk updates happen when annual industry reports are released. Test data synchronizes in batches. Documents fall into three main types. These are structured parameter tables, long-form technical descriptions, and test reports with formulas. Documents include standard fields. These fields are equipment model, performance parameters, finalization time, and test batch number. Most parameters have clear units. Examples include kilometers, rounds per minute.

What constraints these characteristics impose on knowledge base retrieval and recall

Structured parameters in GJB documents and finalization reports require field-level exact matching. Fuzzy matching would cause parameter deviations, so exact matching is needed. Long-form technical and test reports have high word counts. Split documents reasonably. Overly long single segments reduce recall accuracy. The non-periodic update schedule needs incremental synchronization support. Full index rebuilding causes performance loss, so incremental sync avoids this. Performance parameters use multiple units. Unify unit formatting before retrieval. This ensures consistent parameter units in recall results. Test batch numbers require associated retrieval. The recall link must support multi-field combined filtering. This accurately locates test data from the same batch.

How to set configurations

Configuration Item	Recommended Value	Rationale
`Recall count`	`Top 10-15 entries`	Ordnance equipment documents mostly contain precise parameters. Too many recalled entries introduce irrelevant data. Too few fail to cover the full parameter set
`Similarity threshold`	`0.75-0.85`	Structured parameter matching requires high precision. This avoids recalling incorrect parameters with low similarity
`Chunk size`	`800-1200 characters`	Splitting long test reports retains complete parameter context. It also prevents semantic fragmentation from overly long single segments
`Rerank result count`	`Top 5-8 entries`	Investment research scenarios need precise results for core parameters. Reranking filters low-relevance content from initial recall results
`Incremental sync interval`	`Every 6 hours`	New equipment finalization nodes are irregular. Incremental synchronization updates data timely and reduces server load
`Single Document Max Parse Character Count`	`50000 characters`	Adapts to long finalization reports and test data. This prevents parsing truncation that loses critical information

The parameter values provided on this page are general recommendations to use as a starting point for configuration. Actual values are affected by material format, data volume, and business rules. Specific issues require individual analysis. It is recommended to test on your own samples before finalizing settings.

Three common errors

Issue: Retrieval response time exceeds 10 seconds, and reaches 15 seconds in some scenarios. Cause: The Recall count and Chunk size parameters were not adjusted. Too many documents are recalled per batch and single segments are too long, leading to excessive computational load in vector retrieval and reranking steps.
Issue: After upgrading to version 4.8.12, calling the knowledge base question answering interface returns an incomplete error in the format error: { 2024-12-. Cause: Compatible configurations for the knowledge base vector index were not synchronized after the version update, and full error log output configuration was not enabled, leading to truncated error messages.
Issue: Recall results contain inconsistent parameter units, such as range values shown in both kilometers and meters. Cause: Retrieval rules for unified unit matching were not configured, and field-level parameter verification logic was not enabled, leading to fuzzy matching introducing documents with incorrect units.

How to confirm the configuration is correct

Submit a retrieval request that includes specific equipment models and performance parameters. Check whether the recalled documents contain exact matching content for the corresponding fields.
Check the retrieval response time. Compare the duration before and after adjusting the configuration to confirm performance meets expectations.
Check the knowledge base index status after a version update. Confirm that the vector database connection and synchronization status are normal.
Test uploading and parsing documents of different lengths. Confirm that single documents are not truncated and segments meet configuration requirements.

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.