Ontologies in the era of large language models – a perspective

IF 2.5 4区计算机科学 Q3 COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE

Applied Ontology Pub Date : 2023-12-29 DOI:10.3233/ao-230072

Fabian Neuhaus

引用次数: 0

Abstract

The potential of large language models (LLM) has captured the imagination of the public and researchers alike. In contrast to previous generations of machine learning models, LLMs are general-purpose tools, which can communicate with humans. In particular, they are able to define terms and answer factual questions based on some internally represented knowledge. Thus, LLMs support functionalities that are closely related to ontologies. In this perspective article, I will discuss the consequences of the advent of LLMs for the field of applied ontology.

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大型语言模型时代的本体论--一个视角

大型语言模型（LLM）的潜力吸引了公众和研究人员的想象力。与前几代机器学习模型相比，大型语言模型是一种通用工具，可以与人类交流。特别是，它们能够根据一些内部知识定义术语并回答事实性问题。因此，LLM 支持与本体密切相关的功能。在这篇文章中，我将讨论 LLMs 的出现对应用本体论领域的影响。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

Applied Ontology COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE-COMPUTER SCIENCE, INFORMATION SYSTEMS

CiteScore

4.80

自引率

30.00%

发文量

审稿时长

>12 weeks

期刊介绍： Applied Ontology focuses on information content in its broadest sense. As the subtitle makes clear, two broad kinds of content-based research activities are envisioned: ontological analysis and conceptual modeling. The former includes any attempt to investigate the nature and structure of a domain of interest using rigorous philosophical or logical tools; the latter concerns the cognitive and linguistic structures we use to model the world, as well as the various analysis tools and methodologies we adopt for producing useful computational models, such as information systems schemes or knowledge structures. Applied Ontology is the first journal with explicit and exclusive focus on ontological analysis and conceptual modeling under an interdisciplinary view. It aims to establish a unique niche in the realm of scientific journals by carefully avoiding unnecessary duplication with discipline-oriented journals. For this reason, authors will be encouraged to use language that will be intelligible also to those outside their specific sector of expertise, and the review process will be tailored to this end. For example, authors of theoretical contributions will be encouraged to show the relevance of their theory for applications, while authors of more technological papers will be encouraged to show the relevance of a well-founded theoretical perspective. Moreover, the journal will publish papers focusing on representation languages or algorithms only where these address relevant content issues, whether at the level of practical application or of theoretical understanding. Similarly, it will publish descriptions of tools or implemented systems only where a contribution to the practice of ontological analysis and conceptual modeling is clearly established.