13 citations · 16 across the 7 of their papers we have counts for
4 papers · 1 filter
Assisted Data Annotation for Business Process Information Extraction from Textual Documents
Julian Neuberger, Han van der Aa, Lars Ackermann +3
Machine-learning based generation of process models from natural language text process descriptions provides a solution for the time-intensive and expensive process discovery phase…
A Universal Prompting Strategy for Extracting Process Model Information from Natural Language Text using Large Language Models
Julian Neuberger, Lars Ackermann, Han van der Aa +1
Over the past decade, extensive research efforts have been dedicated to the extraction of information from textual process descriptions. Despite the remarkable progress witnessed i…
Leveraging Data Augmentation for Process Information Extraction
Julian Neuberger, Leonie Doll, Benedict Engelmann +2
Business Process Modeling projects often require formal process models as a central component. High costs associated with the creation of such formal process models motivated many…
Beyond Rule-based Named Entity Recognition and Relation Extraction for Process Model Generation from Natural Language Text
Julian Neuberger, Lars Ackermann, Stefan Jablonski
Process-aware information systems offer extensive advantages to companies, facilitating planning, operations, and optimization of day-to-day business activities. However, the time-…