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Use a Noul when the answer is yes or no. For example, does this message ask for a refund, does this resume mention distributed systems, does this comment contain personal data. If the answer is one of several options, use a Choice. If it’s a position on a spectrum, use a Score. Choose a question type compares all three. A Noul answer is a single number, noul, the probability that the answer is yes.

Writing a Noul question

A Noul evaluates a single yes/no question (or statement). It is defined by its instructions: the yes/no question to evaluate. It’s good practice to phrase it so a high probability means “yes”, so that the returned answer is unambiguous in its meaning. You can optionally add criteria with true and false descriptions to clarify what each outcome means, which can be helpful when the question itself has more nuance to explain. Try your Noul prompts with and without criteria to see which works better in your use-case.

Request

Response

noul ranges from 0 to 1, representing the probability that the answer is yes. Most often you will threshold it into a boolean when your code needs a hard decision.

Noul does not return a separate confidence value

A value near 1 means a strong yes. A value near 0 means a strong no. A value near 0.5 gives yes and no similar probability. For “Is the candidate strong in Python?”, define what “strong” means. An unclear definition makes the probability hard to interpret. A value of 0.5 does not mean medium skill. Use a Score to measure skill along defined levels. Choose a question type explains the distinction.

Example questions

Tips and advanced usage

  • Phrasing. Beyond a plain question, you can phrase the instruction as a statement for the model to evaluate for truthfulness. For “the customer is requesting a refund”, a value near 1 means the statement is true. Try both phrasings with your own data to see what works best.
  • Optional criteria. The instruction is enough for most Noul questions, but when the boundary between yes and no is subtle, pass criteria with true and false descriptions to pin down what each outcome means — as shown in the request example above.