化学蛋白相互作用提取的端到端模型:更好的代币化和基于跨度的管道策略
Xuguang Ai1, Ramakanth Kavuluru2
1Department of Computer Science, University of Kentucky, Lexington, USA.
概括
这项研究引入了一个新的生物医学文本端到端关系提取 (E2ERE) 管道,在ChemProt数据集上取得了最先进的结果. 我们的方法通过有效处理复杂的命名实体,显著提高了性能.
科学领域:
- 生物医学自然语言处理
- 提取信息 提取信息
- 计算生物学 计算生物学
背景情况:
- 科学文献的指数增长需要先进的信息提取技术.
- 端到端的关系提取 (E2ERE) 对于识别实体及其关系至关重要,与传统的关系提取 (RE) 不同,它假定预先识别的实体.
- ChemProt数据集在生物医学文本中对E2ERE提出了复杂的挑战,重点是化学基因/蛋白质相互作用.
研究的目的:
- 为生物医学领域开发和评估一套最先进的端到端关系提取系统.
- 改进现有的E2ERE在具有挑战性的ChemProt数据集上的性能.
- 调查细粒度令牌化对基于跨度的E2ERE方法的影响.
主要方法:
- 基于跨度的管道方法被用于端到端的关系提取.
- 使用细粒度的代币化来增强对复杂的命名实体的处理.
- 拟议的方法在ChemProt数据集上进行了评估,ChemProt数据集是生物医学E2ERE的标准基准.
主要成果:
- 开发的E2ERE系统在ChemProt数据集上取得了新的最先进的性能.
- 与之前的最佳努力相比,F1得分明显改善了4%以上.
- 细粒度的代币化对于基于跨度的E2ERE来说是有益的,特别是对于复杂的实体来说.
结论:
- 拟议的基于跨度的管道方法为生物医学端到端关系提取提供了强大的解决方案.
- 精细的代币化是提高E2ERE性能的一个关键因素,特别是在复杂的命名实体中.
- 进一步的分析为ChemProt数据集确定了E2ERE中的特定故障模式,指导了未来的研究.
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