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arXiv.org e-Print Archive
Preprint . 2023
Data sources: arXiv.org e-Print Archive
https://dx.doi.org/10.48550/ar...
Article . 2023
License: CC BY SA
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Conversational Ontology Alignment with ChatGPT

descriptionPublicationkeyboard_double_arrow_right Article , Preprint 01 Jan 2023Embargo end date: 01 Jan 2023Publisher:arXivFunded by:NSF | A1: KnowWhereGraph: Enric...
Authors: Norouzi, Sanaz Saki; Mahdavinejad, Mohammad Saeid; Hitzler, Pascal;

doi: 10.48550/arxiv.2308.09217

arXiv: http://arxiv.org/abs/2308.09217

Conversational Ontology Alignment with ChatGPT

Abstract

This study evaluates the applicability and efficiency of ChatGPT for ontology alignment using a naive approach. ChatGPT's output is compared to the results of the Ontology Alignment Evaluation Initiative 2022 campaign using conference track ontologies. This comparison is intended to provide insights into the capabilities of a conversational large language model when used in a naive way for ontology matching, and to investigate the potential advantages and disadvantages of this approach.

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Keywords

FOS: Computer and information sciences, Computer Science - Computation and Language, Computation and Language (cs.CL)

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green