CO-Fun: A German Dataset on Company Outsourcing in Fund Prospectuses for Named Entity Recognition and Relation Extraction

Neda Foroutan, Markus Schröder, Andreas Dengel


Anthology ID:
2024.konvens-main.13
Volume:
Proceedings of the 20th Conference on Natural Language Processing (KONVENS 2024)
Month:
September
Year:
2024
Address:
Vienna, Austria
Editors:
Pedro Henrique Luz de Araujo, Andreas Baumann, Dagmar Gromann, Brigitte Krenn, Benjamin Roth, Michael Wiegand
Venue:
KONVENS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
117–122
Language:
URL:
https://aclanthology.org/2024.konvens-main.13
DOI:
Bibkey:
Cite (ACL):
Neda Foroutan, Markus Schröder, and Andreas Dengel. 2024. CO-Fun: A German Dataset on Company Outsourcing in Fund Prospectuses for Named Entity Recognition and Relation Extraction. In Proceedings of the 20th Conference on Natural Language Processing (KONVENS 2024), pages 117–122, Vienna, Austria. Association for Computational Linguistics.
Cite (Informal):
CO-Fun: A German Dataset on Company Outsourcing in Fund Prospectuses for Named Entity Recognition and Relation Extraction (Foroutan et al., KONVENS 2024)
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PDF:
https://aclanthology.org/2024.konvens-main.13.pdf