Fig. 1
From: Dynamic Retrieval Augmented Generation of Ontologies using Artificial Intelligence (DRAGON-AI)
The DRAGON-AI ontology term completion process. (1) As an initial preprocessing step, knowledge resources (such as ontologies and GitHub issues) are indexed in a vector database. (2) A user provides a partial ontology term object (here, a term with only the label of the desired term “hydroxyprolinuria” is provided). (3) The vector database is queried for similar terms (e.g. cystathioninuria, hydroxyproline) or other relevant pieces of information (e.g. a GitHub issue). (4) A prompt is generated from a template, incorporating the most similar items in the vector database. (5) The prompt is provided as textual input to an LLM, which returns a completed JSON object. Either local or remote LLMs can be used. (6) The parsed object is returned to the user. Note that this figure uses YAML syntax to represent JSON objects, for the sake of compactness