Completeness Evaluation Criteria

AI agents can be used to measure the completeness of responses. You can read about how the AI agents conduct evaluations as per the defined evaluation criteria here.

The following table describes the evaluation categories and their definitions. The AI agents will categorize each data point into one of the following categories. The power of agents is to conduct semantic evaluations that require complex reasoning and content understanding.

Evaluation Categories	Definitions
Incomplete	The generated response does not include all the information present in the correct response.
Complete	All the information in the correct answer is present in the generated answer. No information is missing from the generated answer, which is present in the correct answer.
Additional information	The generated response include information that is not present in the correct response.
Incomplete and Additional information	The generated response includes information that is not present in the correct response. At the same time, the correct response contains information that is not present in the generated response.

You can further customize the categories and definitions as per your use case easily on the Lighthouz Eval Agent framework.