Unveiling Business Processes Control-Flow: Automated Extraction of Entities and Constraint Relations from Text

Diogo de Santana Candido, Diogo de Santana Candido, Hilário Tomaz Alves de Oliveira, Mateus Barcellos Costa

2025

Abstract

Business process models have increasingly been recognized as critical artifacts for organizations. However, process modeling, i.e., the act of creating accurate and meaningful models, remains a significant challenge. As a result, many processes continue to be informally described using natural language text, leading to ambiguities and hindering precise modeling. To address these issues, more formalized models are typically developed manually, a task that requires substantial time and effort. This study proposes a transcription approach that leverages Natural Language Processing (NLP) techniques for the preliminary extraction of entities and constraint relations. A dataset comprising 133 documents annotated with 5,395 expert labels was utilized to evaluate the effectiveness of the proposed method. The experiments focused on two primary tasks: Named Entity Recognition (NER) and relation classification. For NER, the BiLSTM-CRF model, enhanced with Glove and Flair embeddings, delivered the best performance. In the relation classification task, the RoBERTaLarge model achieved superior results, particularly in managing complex dependencies. These findings highlight the potential of NLP techniques to automate and enhance business process modeling.

Paper Citation

in Harvard Style

Candido D., Alves de Oliveira H. and Costa M. (2025). Unveiling Business Processes Control-Flow: Automated Extraction of Entities and Constraint Relations from Text. In Proceedings of the 27th International Conference on Enterprise Information Systems - Volume 2: ICEIS; ISBN 978-989-758-749-8, SciTePress, pages 771-782. DOI: 10.5220/0013435600003929

in Bibtex Style

@conference{iceis25,
author={Diogo Candido and Hilário Alves de Oliveira and Mateus Costa},
title={Unveiling Business Processes Control-Flow: Automated Extraction of Entities and Constraint Relations from Text},
booktitle={Proceedings of the 27th International Conference on Enterprise Information Systems - Volume 2: ICEIS},
year={2025},
pages={771-782},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013435600003929},
isbn={978-989-758-749-8},
}

in EndNote Style

TY - CONF

JO - Proceedings of the 27th International Conference on Enterprise Information Systems - Volume 2: ICEIS
TI - Unveiling Business Processes Control-Flow: Automated Extraction of Entities and Constraint Relations from Text
SN - 978-989-758-749-8
AU - Candido D.
AU - Alves de Oliveira H.
AU - Costa M.
PY - 2025
SP - 771
EP - 782
DO - 10.5220/0013435600003929
PB - SciTePress