Speaker to Dialogue Attribution in Novels by a Large Language Model through Speaker Position Answering Task

Abstract

The speaker to dialogue attribution task, which identifies the speaker of an utterance in a novel, is an essential task for the analysis of novels and their characters. In order to perform this task, it is necessary to attribute character mentions to utterances. This paper applies large language models to the task of determining whether the speaker of the utterance exists in sentences immediately preceding or subsequent to the utterance, and then divides the entire set of utterances into two groups. Among these, for the group of utterances whose speakers are judged to exist in sentences immediately preceding or subsequent to the utterances, it was shown that the large language models can perform the task of attributing character mentions to utterances with higher accuracy compared to the entire set of utterances.