ON AUTOMATED METADATA GENERATION FOR PREPRINTS AND RESEARCH PAPERS
DOI:
https://doi.org/10.5281/Keywords:
open science, metadata, open access, e-libraries, preprints, research texts, feature extraction, large language models, LLM.Abstract
Large Language Models (LLMs) are capable of high-quality extraction of key descriptive components (metadata) from a text of scientific work, including its title, authors, the author affiliations, publication date, keywords, and abstract. The missing components are generated from the text if possible. The paper’s language is detected, and bilingual metadata are obtained with translating between English and Ukrainian where needed. Using LLM GPT-4o mini, a specialized webservice for automatic metadata extraction from research texts has been developed. It processes PDF documents and generates metadata in the international format of Dublin Core. The webservice automates and simplifies the process of submitting publications to the Archive of Preprints of the National Academy of Science (NAS) of Ukraine. The same approach and tool can be used by repositories of research texts for the rapid import of e-libraries and institutional collections that do not contain metadata in right form. It can also be recommended for journal submission automation.
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