Summary of Know: a Real-world Ontology For Knowledge Capture with Large Language Models, by Arto Bendiken
KNOW: A Real-World Ontology for Knowledge Capture with Large Language Models
by Arto Bendiken
First submitted to arxiv on: 30 May 2024
Categories
- Main: Artificial Intelligence (cs.AI)
- Secondary: Computation and Language (cs.CL)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary This paper introduces KNOW, an ontology designed to capture everyday knowledge and augment large language models (LLMs) for real-world generative AI applications like personal assistants. The focus is on human life, covering everyday concerns and major milestones. The initial scope includes established universals such as spacetime and social concepts. The inclusion criteria prioritize universality and utility. The paper compares previous work, including Schema.org and Cyc, highlighting how LLMs already encode commonsense knowledge. Code-generated software libraries for 12 popular programming languages are also provided to enable ontology concept use in software engineering. This design aims to promote AI interoperability with a focus on simplicity and developer experience. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper creates an important tool called KNOW that helps computers understand everyday things people know. It’s like a dictionary for computers, but instead of words, it has concepts about places, events, people, and more. The goal is to make computers better at understanding and helping humans in their daily lives. The people who made KNOW compared it to other systems that try to do the same thing, and they also created special libraries so that computer programmers can use this knowledge in their work. |
