Information Extraction System for Transforming Unstructured Text Data in Fire Reports into Structured Forms: A Polish Case Study

Marcin Mirończuk

2020 Fire Technology, T. 56, s. 545-581

In this paper, the author presents a novel information extraction systemthat analyses fire service reports. Although the reports contain valuable informationconcerning fire and rescue incidents, the narrative information in these reports hasreceived little attention as a source of data. This is because of the challenges associ-ated with processing these data and making sense of the contents through the use ofmachines. Therefore, a new issue has emerged: How can we bring to light valuableinformation from the narrative portions of reports that currently escape the attentionof analysts? The idea of information extraction and the relevant system for analysingdata that lies outside existing hierarchical coding schemes can be challenging forresearchers and practitioners. Furthermore, comprehensive discussion and proposi-tions of such systems in rescue service areas are insufficient. Therefore, the authorcomprehensively and systematically describes the ways in which information extrac-tion systems transform unstructured text data from fire reports into structured forms.Each step of the process has been verified and evaluated on real cases, including datacollected from the Polish Fire Service. The realisation of the system has illustratedthat we must analyse not only text data from the reports but also consider the dataacquisition process. Consequently, we can create suitable analytical requirements.Moreover, the quantitative analysis and experimental results verify that we can (1)obtain good results of the text segmentation (F-measure 95.5%) and classificationprocesses (F-measure 90%) and (2) implement the information extraction process andperform useful analysis