BLEUScorer
Computes BLEU (Bilingual Evaluation Understudy) score between prediction and ground truth. Measures n-gram precision with a brevity penalty, useful for machine translation and text summarization evaluation.
Overview
Computes BLEU (Bilingual Evaluation Understudy) score between prediction and ground truth. Measures n-gram precision with a brevity penalty, useful for machine translation and text summarization evaluation.
Use Cases
- Accuracy benchmarking and validation
How It Works
This scorer uses deterministic rule-based evaluation to validate outputs against specific criteria. It applies predefined rules and patterns to assess the response, providing consistent and reproducible results without requiring LLM inference.
Input Schema
| Parameter | Type | Required | Description |
|---|---|---|---|
| prediction | str | Yes | Generated text to evaluate |
| ground_truth | str | Yes | Reference text for comparison |
Output Schema
| Field | Type | Description |
|---|---|---|
| score | float | BLEU score scaled to 0-10 |
| passed | bool | True if above threshold |
| reasoning | str | Score breakdown |
| metadata | dict | N-gram precision details |
Score Interpretation
Default threshold: 7/10
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Frequently Asked Questions
When should I use this scorer?
Use BLEUScorer when you need to evaluate nlp-metrics and accuracy aspects of your AI outputs. It's particularly useful for accuracy benchmarking and validation.
Why does this scorer need expected output?
This scorer compares the generated output against a known expected result to calculate accuracy metrics.
Can I customize the threshold?
Yes, the default threshold of 7 can be customized when configuring the scorer.
Quick Info
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