size_categories:1K<n<10K format:csv modality:text library:datasets library:pandas library:mlcroissant library:polars region:us
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A Q&A dataset based on (almost) every Paul Graham's essay. Contains 15 questions about startups for each essay (however, can be less for those essays that are small).\
Political and non-startup-related essays were not considered in the dataset. \
The dataset was created synthetically using the `gpt-4-turbo-2024-04-09` model from the OpenAI API using the following prompt:
```
Essay: {essay}
Generate 15 insightful question and answer pairs that encapsulate universal principles, 
strategic insights, and major ideas relevant to startups and entrepreneurship BASED ON THIS ESSAY. 
These Q&A pairs should be crafted in such a way that they can be understood 
and informative without access to any specific document or article, but cover its contents.
Each answer must be detailed, clearly explaining the concepts in 
depth while ensuring relevance to the given essay. Avoid any reference that necessitates having prior 
access to a particular text. FOR EACH MISTAKE THAT INCLUDES ANY MENTION REQUIRING SPECIFIC SOURCE CONTEXT, I WILL KILL ONE KITTEN
If the essay is not related to startups or too political, return an empty json.
Give the answer in a JSON format - here's an example:
{"questions_and_answers": [{"question": "What color is the sky?", "answer": "Blue"}, ...]}
```

Contains **3144** rows, comprised of **1537105** characters.