Error Analysis in ChatGPT’s MARC21 Records: A Study of RDA Conformity
Authors
-
Department of Studies in Library and Information Science, University of Mysore, Mysuru – 570005, Karnataka
B. Niveditha -
Department of Studies in Library and Information Science, University of Mysore, Mysuru – 570005, KarnatakaN. S. Harinarayana
-
Department of Studies in Library and Information Science, University of Mysore, Mysuru – 570005, KarnatakaChikku Balachandran
DOI:
https://doi.org/10.17821/srels/2024/v61i4/171481Keywords:
Artificial Intelligence, Cataloguing, ChatGPT, MARC21, Resource Description and Access, Quality of CataloguingAbstract
This study aims to evaluate the accuracy and quality of MARC21 catalogue records generated by ChatGPT using bibliographic data from title pages. The study will shed light on the effectiveness and reliability of automated cataloguing processes utilising AI technology. This involves examining factors such as correctness, consistency, and adherence to Resource Description and Access (RDA) standards. The analysis highlights variations in error rates across different records. Identifying the underlying causes of errors in records with higher rates can help in implementing targeted improvements to enhance the data quality and consistency of ChatGPT-generated catalogue records.
Downloads
Metrics
References
American Library Association. (2014). Resource Description and Access. American Library Association.
Atlas, S. (2023). ChatGPT for higher education and professional development: A guide to conversational AI. College of Business Faculty Publications. https://digitalcommons.uri.edu/cba_facpubs/548
Bodenhamer, J. (2023). The reliability and usability of ChatGPT for library metadata. ShareOk. https://shareok.org/handle/11244/339626
ChatGPT. (2024). ChatGPT, How well are you trained in MARC21 and RDA? What are your capabilities in understanding RDA records in MARC21 format? OpenAI platform.
Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., …, Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, 102274. https://doi.org/10.1016/j.lindif.2023.102274
Lund, B. D., & Wang, T. (2023). Chatting about ChatGPT: How may AI and GPT impact academia and libraries? Library Hi Tech News, 40(3), 26-29. https://doi.org/10.1108/LHTN-01-2023-0009
Taecharungroj, V. (2023). What Can ChatGPT Do? Analyzing early reactions to the innovative AI Chatbot on Twitter. Big Data and Cognitive Computing, 7(1), 35. https://doi.org/10.3390/bdcc7010035
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2024 Journal of Information and Knowledge
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
All the articles published in Journal of Information and Knowledge are held by the Publisher. Sarada Ranganathan Endowment for Library Science (SRELS), as a publisher requires its authors to transfer the copyright prior to publication. This will permit SRELS to reproduce, publish, distribute and archive the article in print and electronic form and also to defend against any improper use of the article.
