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README.md

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 This dataset contains manually labeled examples used for training and testing [reddgr/tl-test-learn-prompt-classifier](https://huggingface.co/reddgr/tl-test-learn-prompt-classifier), a fine-tuning of DistilBERT that classifies chatbot prompts as either 'test' or 'learn.'
 
-Prompts labeled as 'test' (1) are those where it can be inferred that the user is intentionally 'challenging' the conversational tool with a complicated question the user might know the answer to, or a subjective question the user makes with the purpose of testing the tool rather than learning from it or obtaining a specific unknown information.
+Prompts labeled as 'test' (1) are those where it can be inferred that the user is:
+
+a) Presenting a problem that requires reasoning or arithmetic logic to resolve.
+b) Intentionally 'challenging' the conversational tool with a complicated question the user might know the answer to.
+c) Presenting a highly subjective question the user makes with the purpose of testing the tool rather than learning from it or obtaining a specific unknown information.
+
+Prompts labeled as 'instruction' (0) are those containing straightforward questions or requests where it can be inferred the user expects to learn something or obtain valuable/practical information from the interaction.
 
 An alternative naming convention for the labels is 'problem' (test) vs 'instruction' (learn). The earliest versions of the reddgr/tl-test-learn-prompt-classifier model used a zero-shot classification pipeline for those two specific terms: instruction (0) vs problem (1).