# Generated by API Evangelist (build-phrasing.py). Our phrasing, not observed demand.
overlay: 1.0.0
info:
  title: API Evangelist conversational phrasing for Microsoft Azure ContentSafety Service Text:detect…
  version: 1.0.0
extends: openapi/microsoft-azure-text-detectgroundedness-api-openapi.yml
actions:
- target: $.info
  update:
    x-apievangelist-phrasing:
      method: generated
      generated: '2026-09-26'
      generator: build-phrasing.py
      label: Generated by API Evangelist
      operations: 1
- target: $.paths['/text:detectGroundedness'].post
  update:
    x-apievangelist-phrasing:
      intent: Detect ungrounded content in an LLM response
      effect: read
      questions:
      - How do I check whether a language model's answer is supported by my source documents?
      - Can I get reasoning for why content was flagged as ungrounded?
      - Does groundedness detection work for summarization as well as Q&A?
      instructions:
      - text: Check whether {text} is grounded in sources {sources}.
        slots:
          text: requestBody.text
          sources: requestBody.groundingSources
      - text: Detect hallucinations in {text} against {sources} for task {task}.
        slots:
          text: requestBody.text
          sources: requestBody.groundingSources
          task: requestBody.task
      method: generated
      generated: '2026-09-26'