Prompting Implicit Discourse Relation Annotation

Pre-trained large language models, such as ChatGPT, archive outstanding performance in various reasoning tasks without supervised training and were found to have outperformed crowdsourcing workers. Nonetheless, ChatGPT's performance in the task of implicit discourse relation classification, prompted by a standard multiple-choice question, is still far from satisfactory and considerably inferior to state-of-the-art supervised approaches. This work investigates several proven prompting techniques to improve ChatGPT's recognition of discourse relations. In particular, we experimented with breaking down the classification task that involves …

annotation art chatgpt classification crowdsourcing cs.ai cs.cl discourse found language language models large language large language models multiple performance prompting question reasoning s performance standard state supervised training tasks training workers