论文标题
环境索赔检测
Environmental Claim Detection
论文作者
论文摘要
要过渡到绿色经济，公司提出的环境要求必须可靠，可比和可验证。为了大规模分析此类主张，需要自动化方法来首先检测它们。但是，对于此而言，没有数据集或模型。因此，本文介绍了环境主张检测的任务。为了伴随任务，我们发布了在此数据集上培训的专家注册数据集和模型。我们预览了此类模型的一种潜在应用：我们检测到季度收入电话中提出的环境主张，发现自2015年巴黎协定以来，环境索赔的数量稳步增加。
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.
