论文标题
自动文本证据挖掘在19.19文献中
Automatic Textual Evidence Mining in COVID-19 Literature
论文作者
论文摘要
我们创建了这个Evidenceminer系统，用于在Covid-19文献中自动文本证据挖掘。 EvidenceMiner是一个基于Web的系统，可让用户查询自然语言语句，并自动从背景语料库中检索生命科学的文本证据。它以一种完全自动化的方式构建，而无需任何人力训练数据注释。 Evidenceminer受到新的数据驱动方法的支持，用于远距离监督的命名实体识别和开放信息提取。指定的实体和元模式是预先计算的，并脱机索引，以支持快速的在线证据检索。注释结果也在原始文档中突出显示，以更好地可视化。 Evidenceminer还包括分析功能，例如最常见的实体和关系摘要。
We created this EVIDENCEMINER system for automatic textual evidence mining in COVID-19 literature. EVIDENCEMINER is a web-based system that lets users query a natural language statement and automatically retrieves textual evidence from a background corpora for life sciences. It is constructed in a completely automated way without any human effort for training data annotation. EVIDENCEMINER is supported by novel data-driven methods for distantly supervised named entity recognition and open information extraction. The named entities and meta-patterns are pre-computed and indexed offline to support fast online evidence retrieval. The annotation results are also highlighted in the original document for better visualization. EVIDENCEMINER also includes analytic functionalities such as the most frequent entity and relation summarization.
