Using LLMs to Convert Unstructured Data Into Structured Data One of the most common use cases for Enterprise AI is NER, or named entity extraction. It's particularly useful when combined with transcription if you run a call center - you transcribe the call and then extract key terms. Much... See more

Here’s how the LinkedIn Engineering team reduced the error rate from ~10% to ~0.01% when generating structured outputs with LLMs. Turning natural text into structured outputs is a cool use case for LLMs. But getting LLMs to do this reliably is quite challenging. https://t.co/FOgEWE4K3Y