用ChemDataExtractor和雪球算法自动生成的库里和尼尔温度数据集
Charles R Kelly1, Jacqueline M Cole2,3
1Cavendish Laboratory, University of Cambridge, J. J. Thomson Avenue, Cambridge, CB3 0HE, UK.
Scientific data
|December 12, 2025
概括
采矿科学论文创建了一个新的库里和尼尔温度数据集. 该资源将帮助研究人员设计和分析磁性材料.
科学领域:
- 材料科学 材料科学 材料科学
- 计算化学计算化学
- 数据科学数据科学数据科学
背景情况:
- 基里和尼尔温度是磁性材料的关键参数.
- 从文献中手动提取这些温度是耗时且容易出现错误的.
- 需要一个全面的,机器可读的数据集来加速研究.
研究的目的:
- 创建一个大规模的,自动生成的库里和尼尔温度数据集.
- 为材料科学界提供有价值的资源.
- 为了证明自动化文本挖掘用于科学数据提取的有效性.
主要方法:
- 使用了ChemDataExtractor 2.2.2工具包和一个雪球v2解析器.
- 开发了一种化学意识的自然语言处理方法.
- 从108,181篇科学文章中提取了56,037条化学实体及其相关温度记录.
主要成果:
- 创建了一个数据集,包含56,037个基里和尼尔温度记录.
- 在数据提取中实现了72%的精度和61%的回忆.
- 该数据集是首次使用Snowball v2解析器进行此特定任务的数据集.
结论:
- 自动生成的数据集有助于设计,预测和分析磁性材料.
- 使用NLP工具的自动数据提取为科学数据的策划提供了一个可扩展的解决方案.
- 这一数据集的公开可用性将促进磁性材料研究的进步.
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