Input | |||
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Required Input | Type | Description | |
context | string | The context provided to the model | |
output | string | The output generated by the model |
Output | ||
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Field | Description | |
Result | Returns a score, where higher scores indicate stronger adherence to the context | |
Reason | Provides a detailed explanation of the context adherence assessment |
What to do when Context Adherence is Low
When context adherence is low, start by identifying statements that are not supported by the provided context and checking for implicit versus explicit information to assess potential misinterpretations. Reviewing how the context is processed can help pinpoint inconsistencies. If necessary, expand context coverage to fill in gaps, clarify ambiguous details, and add missing relevant information. To improve adherence, implement stricter context binding, integrate fact-checking mechanisms, and enhance overall context processing.Comparing Context Adherence with Similar Evals
- Context Relevance: While Context Adherence focuses on staying within context bounds, Context Relevance evaluates if the provided context is sufficient and appropriate for the query.
- Prompt/Instruction Adherence: Context Adherence measures factual consistency with context, while Prompt Adherence evaluates following instructions and format requirements.