What data for this category looks like
This category of data typically comes from audio files, annotation platforms, specialized term lists, and spot-check samples. Daily maintained documents include transcription specifications, audio delivery lists, quality inspection reports, and speaker annotation forms. Data updates occur daily or per annotation batch. Common data fields include audio duration, annotator ID, quality inspection score, and specialized term annotation results, with units such as seconds, entries, and characters. Overall data primarily combines structured annotation results and associated audio metadata, differing from plain text data sources used in pure text annotation projects.
Constraints Imposed by These Data Characteristics on Knowledge Base Retrieval and Recall
The data characteristics of this category create multi-dimensional constraints for knowledge base retrieval and recall. Audio-related metadata such as duration and source channel must be included in retrieval matching scopes. This prevents matching only text content while ignoring context from associated audio. High-frequency updates daily or per batch require the retrieval system to support incremental synchronization, reducing resource use from full reindexing. Specialized term list documents require retrieval logic to apply weighted processing to specialized terms, lowering missed recall rates. When multiple document types are stored together, retrieval systems must support filtering results by document type, avoiding irrelevant quality inspection reports interfering with annotation-related retrieval requests.
How to Set Configurations
This page’s configurations are based on FastGPT v4.17.0.
| Configuration Item | Recommended Value Range | Rationale |
|---|---|---|
similarity | 0.72–0.85 | This category has a high proportion of specialized terms. This range balances the accuracy of specialized term matching and coverage of general content recall, avoiding excessive irrelevant results from too low a value, and missed specialized term recall from too high a value |
limit | Top 6–8 entries | Speech annotation documents contain many metadata fields. This value range controls the total character count of single-round retrieval results, adapting to conversation context window limits |
usingReRank | Enabled | This category of data contains a large number of similar annotation specification entries. Reranking filters semantically duplicate results, improving information readability for pre-sales Q&A |
datasetSearchUsingExtensionQuery | Enabled | Automatically expands user pre-sales or technical support questions, adding specialized term prefixes related to annotations, improving recall effectiveness for low-confidence questions |
collectionIds | Specified per the annotation team’s exclusive knowledge base collection | Separates data from different customer annotation projects, avoiding interference from cross-project documents, adapting to multi-tenant scenarios for private deployments |
Three Common Misconfigurations
- Symptom: An exact text match in the knowledge base fails to return during retrieval, but works normally after creating a new knowledge base of the same type. Cause: The original knowledge base’s
collectionIdsconfiguration binds to an incorrect document collection, so the retrieval scope does not cover the target documents. - Symptom: When calling the API to set the
limitparameter above 6, the private deployment environment cannot return more than 6 results. Cause: The retrieval upper limit threshold was not adjusted in system configuration, with the default limit set to 6 entries. - Symptom: No results return for retrieval requests targeting specialized terms. Cause:
datasetSearchUsingExtensionQueryis not enabled, so no specialized term matching prefixes are automatically added, preventing correct identification of specialized terms.
How to Confirm Configurations Are Set Properly
- Initiate a retrieval request that includes specialized terms, and verify that returned results include the corresponding annotation specification or term list documents.
- View retrieval logs to confirm the
similarityparameter’s matching threshold falls within the preset range, with no abnormal filtering. - Call the API with a custom
collectionIdsvalue, and verify returned results only come from the specified knowledge base collection. - After enabling
usingReRank, compare result duplication rates before and after activation to confirm the reranking function works.
The values provided are common starting points and should be measured 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 2026-10-19.