Evaluate factual consistency
POST/v2/evaluate_factual_consistency
Evaluates the factual consistency of a generated text (like a summary) against source documents. The evaluation determines how accurately the generated text reflects the information in the source documents. This helps identify potential hallucinations or misrepresentations.
Use this endpoint to validate generated content against trusted source materials, such as in legal, healthcare, scientific publishing, and enterprise knowledge systems.
The request body includes the following parameters:
model_parameters.model_name: Optional. The evaluation model to use.hhem_v2.3is the default and the recommended model.hhem_v2.2is retired; it remains accepted for backward compatibility and is served byhhem_v2.3. Any other value is rejected with a400.generated_text: The output text you want to evaluate, such as a model-generated summary, answer, or response.source_texts: An array of source documents or passages used to verify the accuracy of the generated text.
The endpoint scores the texts as given, in whatever language they are written. HHEM is trained on eng, deu, fra, spa, por, ara, kor, zho, rus, jpn, and hin; treat scores for text in other languages as unreliable.
Example request
This example evaluates whether a generated statement about the Eiffel Tower is factually accurate based on two reference documents.
{
"generated_text": "The Eiffel Tower is located in Berlin.",
"source_texts": [
"The Eiffel Tower is a famous landmark located in Paris, France.",
"It was built in 1889 and remains one of the most visited monuments in the world."
]
}
Example response
The response includes the factual consistency score.
{
"score": 0.23
}
score: A normalized value between0.0and1.0that reflects the overall factual alignment between the generated text and the source texts. Higher scores indicate stronger consistency.
Request
Responses
- 200
- 400
- 403
The factual consistency evaluation results.
Invalid request body.
Permissions do not allow factual consistency evaluation.