Construct relation extraction from scientific papers: Is it automatable yet?

Publikation: Beiträge in SammelwerkenAbstracts in KonferenzbändenForschungbegutachtet

Authors

The process of identifying relevant prior research
articles is crucial for theoretical advancements, but
often requires significant human effort. This study
examines the feasibility of using large language
models (LLMs) to support this task by extracting
tested hypotheses, which consist of related constructs,
moderators or mediators, path coefficients, and
p-values, from empirical studies using structural
equation modeling (SEM). We combine state-of-the-art
LLMs with a variety of post-processing measures
to improve the relation extraction quality. An
extensive evaluation yields recall scores of up to
79.2% in construct entity extraction, 58.4% in
construct-mediator/moderator-construct extraction,
and 39.3% in extracting the full tested hypotheses.
We provide a manually annotated dataset of 72 SEM
articles and 749 construct relations to facilitate future
research. Our findings offer critical insights and
suggest promising directions for advancing the field of
automated construct relation extraction from scholarly
documents.
OriginalspracheEnglisch
TitelProceedings of the 58th Hawaii International Conference on System Sciences
HerausgeberTung Bui
Anzahl der Seiten10
ErscheinungsortHonolulu
VerlagUniversity of Hawaii at Manoa
Erscheinungsdatum07.01.2025
Seiten4675-4684
ISBN (elektronisch)978-0-9981331-8-8
PublikationsstatusErschienen - 07.01.2025
Veranstaltung58th Hawaii International Conference on System Sciences - HICSS 2025 - Hilton Waikoloa Village, Waikoloa, USA / Vereinigte Staaten
Dauer: 07.01.202510.01.2025
Konferenznummer: 58

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  14. IdeenExpo 2015
  15. International Week: Fall International Talks - IULM 2011
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  17. SASE 2021 – Virtual Conference
  18. World Universities Congress 2010
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  20. Informatik-Spektrum (Zeitschrift)
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