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Prompt-Time Ontology-Driven Symbolic Knowledge Capture with Large Language Models
Published 22 May 2024 in cs.AI and cs.CL | (2405.14012v1)
Abstract: In applications such as personal assistants, LLMs must consider the user's personal information and preferences. However, LLMs lack the inherent ability to learn from user interactions. This paper explores capturing personal information from user prompts using ontology and knowledge-graph approaches. We use a subset of the KNOW ontology, which models personal information, to train the LLM on these concepts. We then evaluate the success of knowledge capture using a specially constructed dataset. Our code and datasets are publicly available at https://github.com/HaltiaAI/paper-PTODSKC
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