Facet-based scientific summarization Dataset (FD)
收藏arXiv2024-02-22 更新2024-08-06 收录
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http://arxiv.org/abs/2402.14359v1
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资源简介：
Facet-based scientific summarization Dataset (FD)是由阿卜杜拉国王科技大学等机构创建的数据集，包含500个摘要，这些摘要由不同的模型为100篇来自PubMed和arXiv的论文生成。数据集旨在为科学论文摘要的评估提供一个基准，特别是在评估摘要的不同方面，如背景、方法、结果和结论。数据集的创建过程涉及对摘要进行细致的人工标注，以识别和突出不同方面的内容。该数据集的应用领域主要集中在科学论文摘要的自动评估，旨在解决传统评估方法在理解和解释科学概念方面的不足。
Facet-based scientific summarization Dataset (FD) was developed by King Abdullah University of Science and Technology (KAUST) and other institutions. It consists of 500 summaries generated by various models for 100 papers sourced from PubMed and arXiv. This dataset serves as a benchmark for the evaluation of scientific paper summaries, with a particular focus on assessing distinct aspects of summaries including background, methodology, results, and conclusions. The dataset construction process entails meticulous manual annotation of summaries to identify and highlight these distinct content facets. Its primary application domain lies in the automatic evaluation of scientific paper summaries, aiming to address the limitations of traditional evaluation methods in comprehending and interpreting scientific concepts.
提供机构：
阿卜杜拉国王科技大学
创建时间：
2024-02-22
