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["correct","The answer correctly explains how to log a prediction using the Python SDK. It mentions the `arize.log()` function and lists all the necessary parameters that need to be provided, such as `prediction_id`, `model_id`, `model_type`, `environment`, `model_version`, `prediction_timestamp`, `features`, `prediction_label`, and `tags`. It also correctly states that the actual label can be logged by using the `arize.log()` function again and providing the `actual_label` parameter. This is all in line with the information provided in the reference text.",0,"c430c6cc-1027-4a8f-a31b-280e0b285dbc"]
["correct","The question asks for the cost of an enterprise license of Arize. The reference text does not provide any specific information about the cost of an enterprise license. The answer provided also does not give a specific cost, but instead suggests contacting Arize's sales team for detailed pricing information. Therefore, while the answer does not provide a specific cost, it does provide a way to obtain that information, which is the best possible answer given the information available in the reference text.",0,"23a8a063-124f-4f13-a030-bb61d9d7f8f7"]
["incorrect","The reference text does not provide any information on how to delete a model. It only provides information on how to navigate to the custom metric editor and what can be found there. The answer, on the other hand, provides a general method on how to delete a model, but it does not match the information given in the reference text. Therefore, the answer is incorrect.",0,"f31c335f-9b7f-4ed7-96eb-ace33a4df064"]
["correct","The reference text provides a GraphQL query example where the 'status' field is included in the query. This query is used to get the status of a monitor. Therefore, the given answer correctly states that you can query for a monitor's status using GraphQL by including the 'status' field in your query.",0,"bce5b9ae-4587-4ead-9ccc-de3fe29257bc"]