2026-05-25T09:51:35Z https://datacatalogue.cessda.eu/oai-pmh/v0/oai

0643e7c0a1f2dd7f42d44235b3dd4d0f65a4a9481e1ab90ca9bbce3a2146bdcc 2026-02-09T03:09:27Z language:enopenaire_data

DDI study level documentation for study 10.7802/2990 Web Survey: Data Annotation Bottleneck and Active Learning for Natural Language Processing in the Era of Large Language Models Web Survey: Data Annotation Bottleneck and Active Learning for Natural Language Processing in the Era of Large Language Models Web Survey: Data Annotation Bottleneck and Active Learning for Natural Language Processing in the Era of Large Language Models 10.7802/299010.7802/299010.7802/299010.7802/2990 Romberg, Julia Romberg, Julia Schröder, Christopher Schröder, Christopher Gonsior, Julius Gonsior, Julius GESIS Data Archive for the Social SciencesGESIS Datenarchiv für Sozialwissenschaften large language modelssupervised learningdata annotationactive learningpractical applicationlarge language modelssupervised learningdata annotationactive learningpractical application We publish a dataset of 144 community perspectives on the need for annotated training data in the field of Natural Language Processing (NLP). The dataset documents how large language models (LLMs) have impacted the persistent issue of the lack of annotated data. Additionally, we inquire about the current state of the "active learning" annotation method. Our target group consists of experts from academia, industry, and government institutions. The data was collected with a web survey that was open online to voluntary participants for 6 weeks, from December 15th, 2024, to January 26th, 2025. keywords: large language models, supervised learning, data annotation, active learning, practical applicationWe publish a dataset of 144 community perspectives on the need for annotated training data in the field of Natural Language Processing (NLP). The dataset documents how large language models (LLMs) have impacted the persistent issue of the lack of annotated data. Additionally, we inquire about the current state of the "active learning" annotation method. Our target group consists of experts from academia, industry, and government institutions. The data was collected with a web survey that was open online to voluntary participants for 6 weeks, from December 15th, 2024, to January 26th, 2025. keywords: large language models, supervised learning, data annotation, active learning, practical application Experts in Natural Language Processing Selbstausfüller:CAWI(Computerunterstütztes Web-Interview)Selbstausfüller:CAWI(Computerunterstütztes Web-Interview) Free access (with registration) - The research data can be downloaded by registered users. CC BY-NC-SA 4.0: Namensnennung - Nicht kommerziell – Weitergabe unter gleichen Bedingungen (https://creativecommons.org/licenses/by-nc-sa/4.0/deed.de)Freier Zugang (mit Registrierung) - Die Forschungsdaten können von allen registrierten Nutzerinnen und Nutzern heruntergeladen werden. CC BY-NC-SA 4.0: Namensnennung - Nicht kommerziell – Weitergabe unter gleichen Bedingungen (https://creativecommons.org/licenses/by-nc-sa/4.0/deed.de) http://dbkapps.gesis.org/dbkoai/oai.asp oai:dbk.gesis.org:SDN/10.7802_2990 2026-01-31 ddi:codebook:2_5