CoastTerm：一个用于沿海科学文献中多学科术语提取的语料库
CoastTerm: a Corpus for Multidisciplinary Term Extraction in Coastal Scientific Literature
AI总结：
本文构建包含410篇沿海科学摘要、2,491个句子的CoastTerm语料库，并基于ARDI框架使用单语与多语transformer完成ATE和ATC，F1分别约达80%和70%。
摘要：
气候变化对沿海地区（尤其是活跃但脆弱的区域）日益增大的影响，要求不同利益相关方和学科开展协作，以制定有效的环境保护政策。我们介绍了一个新颖的专用语料库，包含来自410篇涉及沿海地区的科学摘要的2,491个句子，用于自动术语提取（ATE）和分类（ATC）任务。受ARDI框架启发——该框架聚焦于识别行动者、资源、动态和相互作用——我们利用单语和多语transformer模型，自动提取领域术语及其在沿海系统运行中的不同角色。评估显示结果稳定一致，自动术语提取取得约80%的F1分数，提取术语及其标签取得70%的F1分数。这些发现令人鼓舞，标志着朝着构建专用于沿海地区的专用知识库迈出了初步一步。
英文摘要：
The growing impact of climate change on coastal areas, particularly active but fragile regions, necessitates collaboration among diverse stakeholders and disciplines to formulate effective environmental protection policies. We introduce a novel specialized corpus comprising 2,491 sentences from 410 scientific abstracts concerning coastal areas, for the Automatic Term Extraction (ATE) and Classification (ATC) tasks. Inspired by the ARDI framework, focused on the identification of Actors, Resources, Dynamics and Interactions, we automatically extract domain terms and their distinct roles in the functioning of coastal systems by leveraging monolingual and multilingual transformer models. The evaluation demonstrates consistent results, achieving an F1 score of approximately 80\% for automated term extraction and F1 of 70\% for extracting terms and their labels. These findings are promising and signify an initial step towards the development of a specialized Knowledge Base dedicated to coastal areas.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
