at Google ScholarTitle data
Neuberger, Julian ; Herrmann, Jannic ; Käppel, Martin ; van der Aa, Han ; Jablonski, Stefan:
TeaPie: A Tool for Efficient Annotation of Process Information Extraction Data.
In: Comuzzi, Marco ; Grigori, Daniela ; Sellami, Mohamed ; Zhou, Zhangbing
(ed.):
Cooperative Information Systems. -
Cham
: Springer Nature Switzerland
,
2025
. - pp. 405-410
ISBN 978-3-031-81375-7
DOI: https://doi.org/10.1007/978-3-031-81375-7_28
Abstract in another language
Machine-learning based generation of process models from natural language text process descriptions is severely restrained by a lack of datasets. This lack of data can be attributed to, among other things, an absence of proper tool assistance for dataset creation, resulting in high workloads and inferior data quality. We address these shortcomings with a tool for annotating textual process descriptions. Compared to other, existing data annotation tools, ours implements a multi-step workflow specifically designed for extracting process information, including supporting features that have been shown to reduce workloads and improve data quality.
Further data
| Item Type: | Article in a book |
|---|---|
| Refereed: | Yes |
| Keywords: | Process information extraction; Text annotation; Business process management |
| Institutions of the University: | Faculties > Faculty of Mathematics, Physics und Computer Science > Department of Computer Science > Chair Applied Computer Science IV > Chair Applied Computer Science IV - Univ.-Prof. Dr.-Ing. Stefan Jablonski |
| Result of work at the UBT: | Yes |
| DDC Subjects: | 000 Computer Science, information, general works > 004 Computer science |
| Date Deposited: | 15 May 2025 05:55 |
| Last Modified: | 15 May 2025 05:55 |
| URI: | https://eref.uni-bayreuth.de/id/eprint/93568 |