GESIS Leibniz Institute for the Social Sciences: Go to homepage
To top


Jack Culbert (a.k.a. John) is a research associate in the team Information and Data Retrieval (IDR) situated in the department of Knowledge Technologies for the Social Sciences (KTS).

Jack graduated from the university of Nottingham with a Masters degree in Mathematics focusing on pure mathematics, computation and statistics. He has experience research and development and consulting for the development of Natural Language Processing, Machine Learning and Knowledge Graph systems from his previous employment as a Senior AI&ML Engineer at Roke and Data Scientist at Arca Blanca.

Jack is particularly interested in NLP based Information Extraction technologies, including Entity Recognition, Coreference Resolution, Relationship Extraction and Entity Linking, as well as machine learning technologies such as Large Language Models, Attention Networks and Graph Neural Networks for Classification, Extraction, Link Inference and Sentiment Analysis and Explainable AI.

To top



To top
Working and discussion paper

Culbert, Jack, Philipp Mayr-Schlegel, Anne Hobert, Najko Jahn, Nick Haupka, Marion Schmidt, and Paul Donner. 2024. Reference Coverage Analysis of OpenAlex compared to Web of Science and Scopus. doi:

Culbert, Jack. 2023. 4TCT: A 4chan Text Collection Tool. ArXiV Preprint. doi:

To top

Culbert, Jack, Nina Smirnova, and Philipp Mayr-Schlegel. 2024. Indo-German Literature Dataset. doi:


To top
Presentation not at a conference

Culbert, Jack. 2024. "The Reference Coverage Analysis of OpenAlex compared to WoS and Scopus." Broadening Data Sources for Bibliometric Analyses: Recent Results and Further Developments, Hcéres, Paris, 2024-02-29. doi: