📄 Context Relevance¶

metrics.rag.end_to_end.context_relevance

MetricPipeline(
    main_score="score",
    preprocess_steps=[
        Copy(
            field_to_field=[
                [
                "prediction/contexts",
                "references",
                ],
            ],
        ),
        Copy(
            field_to_field=[
                [
                "task_data/question",
                "prediction",
                ],
            ],
        ),
        MultiTypeSerializer(
            field="prediction",
        ),
    ],
    metric="metrics.perplexity_q.flan_t5_small[score_prefix=context_relevance_]",
)

[source]

from unitxt.operators import Copy
from unitxt.serializers import MultiTypeSerializer

Explanation about Copy¶

Copies values from specified fields to specified fields.

Args (of parent class):
field_to_field (Union[List[List], Dict[str, str]]): A list of lists, where each sublist contains the source field and the destination field, or a dictionary mapping source fields to destination fields.

Examples:
An input instance {“a”: 2, “b”: 3}, when processed by Copy(field_to_field={"a": "b"}) would yield {“a”: 2, “b”: 2}, and when processed by Copy(field_to_field={"a": "c"}) would yield {“a”: 2, “b”: 3, “c”: 2}

with field names containing / , we can also copy inside the field: Copy(field="a/0",to_field="a") would process instance {“a”: [1, 3]} into {“a”: 1}

References: metrics.perplexity_q.flan_t5_small