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About Semantic List Contains

This evaluation is designed to evaluate whether the model’s output closely resembles any of the key phrases provided. The metric is especially useful when exact wording may differ but meaning is preserved or the reference is a set of expected keywords.

How Semantic List Contains Evals Work?

  1. Encodes both response and reference text into dense vectors using a SentenceTransformer.
  2. Computes similarity between the response and each phrase using cosine similarity
  3. Compares the result with a configurable threshold (e.g., 0.7)
  4. Returns 1.0 (if exact match) or 0.0 (no match) depending on whether:
    • Any match (match_all = False, default)
    • All match (match_all = True)

What if Semantic List Contains Eval Score is Low?

  • Lower the similarity_threshold value (if your use case allows relaxed semantic matches).
  • Use "match_all"= False if partial coverage is acceptable.