| CPC G06F 16/24575 (2019.01) [G06F 16/248 (2019.01)] | 20 Claims |

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17. A method comprising:
determining, by one or more processors and based on a first asset of a plurality of data assets, a candidate asset set;
generating, based on the candidate asset set and metadata for the candidate asset set, a refined candidate set;
generating, based on the refined candidate set, a prompt for a large language model (LLM); and
receiving, from the LLM and in response to the prompt, a structured list of recommended data assets, the recommended data assets being a subset of the candidate asset set.
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