An Ontology-Based Classification Framework for Situation Extraction from Concrete Pouring Radio Logs

Radio utterances during concrete pouring convey work progress, equipment conditions, hazard signs, and control actions in short units that may include omitted subjects and site expressions. This study presents a proof of concept for a two-layer ontology framework that structures these utterances into linked semantic and situational records. Starting from timestamped radio text linked to terminal and assigned-role information, the first layer classifies expressions into seven semantic axes: work, act, object, target, phenomenon, interjection, and profanity. The second layer derives hazard signals, control actions, and situation states using semantic relations, action-expression conditions, and chronological context. The procedure is implemented through lexical dictionaries and rules and demonstrated with a researcher-constructed one-day virtual log of 25 utterances. Worked examples show how object and target distinctions lead to different hazard or control-action interpretations, and how subsequent reports and instructions are linked to pressure resolution and restart restrictions. Reference comparisons and error analysis examine internal consistency and unresolved mappings within this development case. An exploratory LLM comparison illustrates challenges in mapping field expressions to the defined semantic axes. The proof of concept demonstrates a procedure for converting linked radio text into structured records that can support later review of communicated conditions and instructions. The contribution is the explicit representation and implemented processing sequence, with quantitative metrics serving as diagnostic evidence for the case. Audio acquisition, speech recognition, and field performance remain subjects for subsequent validation.