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JobLens is cool! This past month we had the same idea -- it's been a fun project: https://hnjobs.u-turn.dev

ChatGPT does an incredible job parsing, but then lots of effort goes into normalizing and deduping each field. Long story short, your results look quite good to me!

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Your project looks quite impressive as well, especially the extracted URLs to apply and the candidate profiles, didn't get that far yet :) Automating tedious work like data extraction and transformation is a great use case for LLMs.

Not sure if you found this as well, but gpt-3.5-turbo-016 does a poor job following instructions other than parsing. So, to work around this, we prompt gpt-3.5-turbo with the rules we want applied say an extracted field and then go back to gpt-3.5-turbo-016 to parse with chatgpt functions.

Bottom line, every single post requires approximately 10 different prompts to refine the extraction.

yeah I had the same experience, divide and conquer works better than trying to do everything with a single prompt. Are you interested in comparing notes? Feel free to ping me via the email in my profile :)

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