What this category of data looks like
Data for this category typically comes from audio lists exported from annotation platforms, raw audio files, custom proprietary vocabularies, spot check quality inspection reports, and speaker annotation forms. Daily business documents include transcription specifications, batch audio delivery lists, and single-item quality inspection result tables. Data updates are synced daily or per annotation task batch. Core fields include audio duration (usually tens of seconds to tens of minutes), speaker identifiers, transcribed text segments, and quality inspection check marks. There is no unified fixed unit, and values are adjusted per annotation task batch.
What constraints do these characteristics impose on the knowledge base retrieval and recall link?
The data update frequency for this category is adjusted per annotation task batch. This requires knowledge base retrieval to support incremental synchronization, avoiding full reconstruction that consumes excessive computing resources. Daily business documents include transcription specifications and proprietary vocabularies. Retrieval must prioritize recalling content related to professional terms and annotation rules, to assist with time-consuming tasks such as noise segment judgment and speaker differentiation. Core fields include speaker identifiers and quality inspection marks. Retrieval must support filtering results by business dimension, ensuring returned content matches the current annotation task scenario. The mixed structure of audio metadata and transcribed text also requires retrieval configuration to balance text semantic matching and structured field filtering.
How to configure the settings
The following configurations are based on FastGPT v4.17.0.
| Configuration Item | Suggested Value | Basis for This Setting |
|---|---|---|
similarity | 0.72–0.85 | Semantic similarity threshold for matching voice annotation proprietary terms and transcription specifications, covering conventional terms and scenario-based expressions |
limit | Top 8 entries | Controls the number of returned results, adapting to the concise, fast query needs of operations duty and work order Q&A |
searchMode | Semantic Retrieval | Prioritizes matching semantic association between transcribed text and specifications, while also accounting for keyword matches |
usingReRank | Enabled | Reranks initial recalled results to improve ranking priority of content related to proprietary term proofreading |
datasetSearchUsingExtensionQuery | Enabled | Automatically expands query terms to cover synonyms and common expressions in annotation scenarios |
collectionIds | Configured per task group | Binds knowledge base collections corresponding to the current annotation task, avoiding interference from cross-task content |
Three common mistakes
- Phenomenon: Retrieval results from the platform test page differ from those returned by API calls. Cause: The latest index configuration of the knowledge base has not been synchronized, or the
collectionIdsparameter configuration differs between the test environment and production environment. - Phenomenon: The number of retrieved results does not match the configured
limit. Cause: Confusing the parameter logic between initial recall count and final returned result count, failing to correctly match the configuration item with actual needs. - Phenomenon: Retrieval results include transcription specification content from non-current tasks. Cause: The
collectionIdsis not configured to bind the knowledge base collection corresponding to the current annotation task, resulting in the retrieval scope covering all available datasets.
How to confirm the configuration is correct
- Enter the knowledge base management page, verify whether
collectionIdsis bound to the knowledge base collection corresponding to the current annotation task. - Initiate a test query to confirm that the number of returned results matches the configured
limitvalue. - Check whether the retrieval results include core business documents such as transcription specifications and proprietary vocabularies, and whether the ranking meets expectations.
- View retrieval time consumption logs, confirm that single retrieval time consumption meets the requirements of the business scenario. Adjust the configuration of
similarityorusingReRankto optimize as needed.
The values given 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.