Prediction of event locations from urgent call using large language models

Abstract

In this study, we propose a method to predict locations of road-related events from urgent call data by using large language models. Operators need to identify the location of road-related events from information verbally conveyed by the reporter during the call, and this requires them to have both job experience and geographical knowledge. We aim to construct the framework that predicts the location from urgent calls to alleviate the burden on operators in their operations. Thus, we utilize the large language models with extensive pre-training knowledge to extract location information from the text transcribed using a speech recognition model. We evaluate the proposed method using real urgent call data to assess its effectiveness and highlight the remaining problems of this study.