2023/10/18 by Shumpei Inoue, Inoue, Shumpei, Minh-Tien Nguyen +9 · 1 citation
Computer Science · Decision Sciences · Health Professions · #Computation and Language (cs.CL) #FOS: Computer and information sciences #Occupational Health and Safety Research #Risk and Safety Analysis #Topic Modeling
paper · pdf · doi:10.48550/arxiv.2310.12074
openalex publication_date 2023/10/18 · openalex created_date 2023/10/21 · openalex updated_date 2026/07/28
This paper introduces a new IncidentAI dataset for safety prevention. Different from prior corpora that usually contain a single task, our dataset comprises three tasks: named entity recognition, cause-effect extraction, and information retrieval. The dataset is annotated by domain experts who have at least six years of practical experience as high-pressure gas conservation managers. We validate the contribution of the dataset in the scenario of safety prevention. Preliminary results on the three tasks show that NLP techniques are beneficial for analyzing incident reports to prevent future failures. The dataset facilitates future research in NLP and incident management communities. The access to the dataset is also provided (the IncidentAI dataset is available at: https://github.com/Cinnamon/incident-ai-dataset).