“Carry out an excellent comma broke up tabular database away from buyers study of an excellent dating application with the adopting the articles: first name, last label, many years, town, county, gender, sexual direction, hobbies, number of likes, quantity of fits, big date customer inserted the fresh app, together with user’s score of application anywhere between step one and 5”
GPT-step 3 failed to provide us with one column headers and provided united states a desk with each-most other line which have no guidance and simply cuatro rows off genuine consumer data. Additionally, it provided you about three articles off passions once we were simply looking that, however, to be fair so you’re able to GPT-step 3, i did play with a good plural. All of that becoming told you, the details they performed establish for all of us is not 1 / 2 of crappy – brands and you can sexual orientations tune toward proper genders, the new locations it offered all of us are also within their right claims, and also the dates fall contained in this an appropriate variety.
Hopefully if we bring GPT-step three a few examples it will finest understand just what we have been looking having. Sadly, because of tool restrictions, GPT-3 are unable to realize a whole databases to know and you may make man-made data from, therefore we could only provide it with a few example rows.
“Do a comma split tabular database that have line headers from 50 rows off customer study out-of an online dating software. 0, 87hbd7h, Douglas, Woods, thirty five, Chi town, IL, Men, Gay, (Baking Color Discovering), 3200, 150, , step 3.5, asnf84n, Randy, Ownes, twenty-two, Chicago, IL, Male, Upright, (Running Hiking Knitting), 500, 205, , step three.2”