Transcripts must have personal data found and removed. Which feature fits?
Why D is the answer
PII detection in Azure Language
PII detection identifies personal entities in text and conversations.
In detail
- PII detection finds personal data so that it can be removed.
- Check it on your own document types.
Use case
An illustrative scenario, not a real incident.
A clinic must remove personal data from transcripts. PII detection in Azure Language finds it, and it is removed before storage.
See it in different ways
flowchart TD
A{"Text task"} -->|"Find personal data"| B["PII detection in Azure Language"]
A -->|"Change language"| C["Azure Translator"]
A -->|"Flexible analysis"| D["Language model with a prompt"]mindmap
root((Language tasks))
PII
Azure Language
Translation
Azure Translator
Custom format
Language model with schema
Safety
Groundedness detection
Protected materialflowchart LR S0["Transcript"] --> S1["PII detection"] --> S2["Redact"] --> S3["Store"]
Key point: PII detection finds personal data.
Why the other options are wrong
- A. Semantic ranker
- Semantic ranker orders search results.
- B. Provisioned throughput on a language model
- Provisioned throughput is about capacity.
- C. Image generation
- Image generation is unrelated.