To transition to a green economy, environmental claims made by companies must be reliable, comparable, and verifiable. To analyze such claims at scale, automated methods are needed to detect them in the first place. However, there exist no datasets or models for this. Thus, this paper introduces the task of environmental claim detection. To accompany the task, we release an expert-annotated dataset and models trained on this dataset. We preview one potential application of such models: We detect environmental claims made in quarterly earning calls and find that the number of environmental claims has steadily increased since the Paris Agreement in 2015.

翻译：为向绿色经济转型，企业提出的环境主张必须可靠、可比较且可验证。为大规模分析此类主张，首先需要自动化方法来检测它们。然而，目前尚不存在相关数据集或模型。因此，本文提出了环境主张检测任务。伴随该任务，我们发布了一个专家标注数据集以及基于该数据集训练的模型。我们预览了这类模型的一项潜在应用：检测季度财报电话会议中提出的环境主张，并发现自2015年《巴黎协定》以来，环境主张的数量稳步增长。