grounding_accuracy_span_level.yaml

prompt:
  template: |-
    Your task is to check if a specific Span is accurate to the Evidence.
    Generate 'Accurate' if the Span is accurate when verified according to the Evidence or when there is nothing to verify in the Span.
    Generate 'Inaccurate' if the Span is inaccurate (contradicts the evidence), or cannot be verified.

    **Query**:

    {{user_request}}

    **End of Query**

    **Evidence**

    {{context_document}}

    **End of Evidence**

    **Response**:

    {{response}}

    **End of Response**


    You are currently verifying **Span {{ix+1}}** from the Response.
    **Span {{ix+1}}**:

    {{span}}

    **End of Span {{ix+1}}**


    Is Span {{ix+1}} accurate or inaccurate when verified according to the Evidence? Point to where in the evidence justifies your answer.
  template_variables:
    - user_request
    - context_document
    - response
    - ix
    - span
  metadata:
    description: "An evaluation prompt from the paper 'The FACTS Grounding Leaderboard: Benchmarking LLMs’ Ability to Ground
      Responses to Long-Form Input' by Google DeepMind.\n    The prompt was copied from the evaluation_prompts.csv file from
      Kaggle.\n    This specific prompt elicits a binary accurate/non-accurate classifier on a span level."
    evaluation_method: span_level
    tags:
      - fact-checking
    version: 1.0.0
    author: Google DeepMind
    source: https://www.kaggle.com/datasets/deepmind/FACTS-grounding-examples?resource=download&select=evaluation_prompts.csv
  client_parameters: {}
  custom_data: {}