3 papers
cs.CL2024
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…
cs.LG2024
Attention Please: What Transformer Models Really Learn for Process Prediction
Martin Käppel, Lars Ackermann, Stefan Jablonski +1
Predictive process monitoring aims to support the execution of a process during runtime with various predictions about the further evolution of a process instance. In the last year…
cs.CL2024
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…