arXiv Open Access 2023

Just Tell Me: Prompt Engineering in Business Process Management

Kiran Busch Alexander Rochlitzer Diana Sola Henrik Leopold

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Abstrak

GPT-3 and several other language models (LMs) can effectively address various natural language processing (NLP) tasks, including machine translation and text summarization. Recently, they have also been successfully employed in the business process management (BPM) domain, e.g., for predictive process monitoring and process extraction from text. This, however, typically requires fine-tuning the employed LM, which, among others, necessitates large amounts of suitable training data. A possible solution to this problem is the use of prompt engineering, which leverages pre-trained LMs without fine-tuning them. Recognizing this, we argue that prompt engineering can help bring the capabilities of LMs to BPM research. We use this position paper to develop a research agenda for the use of prompt engineering for BPM research by identifying the associated potentials and challenges.

Topik & Kata Kunci

cs.AI cs.CL cs.LG

Penulis (4)

Kiran Busch

Alexander Rochlitzer

Diana Sola

Henrik Leopold

Format Sitasi

APA MLA BibTeX

Busch, K., Rochlitzer, A., Sola, D., Leopold, H. (2023). Just Tell Me: Prompt Engineering in Business Process Management. https://arxiv.org/abs/2304.07183

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Informasi Jurnal

Tahun Terbit: 2023
Bahasa: en
Sumber Database: arXiv
Akses: Open Access ✓