The NLBSE'25 Tool Competition

We report on the organization and results of the tool competition of the fourth International Workshop on Natural Language-based Software Engineering (NLBSE'25). As in prior editions, we organized the competition on automated code comment classification, with a larger dataset. In this tool competition edition, six teams submitted multiple classification models to automatically classify code comments. The submitted models were fine-tuned and evaluated on a benchmark dataset of 14,875 code comments, respectively. This paper reports details of the competition, including the rules, the teams and contestant models, and the ranking of models based on their average classification performance across issue report and code comment types.