Plumber: A Modular Framework to Create Information Extraction Pipelines

M. Y. Jaradeh, Kuldeep Singh, M. Stocker, S. Auer
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引用次数: 3

Abstract

Information Extraction (IE) tasks are commonly studied topics in various domains of research. Hence, the community continuously produces multiple techniques, solutions, and tools to perform such tasks. However, running those tools and integrating them within existing infrastructure requires time, expertise, and resources. One pertinent task here is triples extraction and linking, where structured triples are extracted from a text and aligned to an existing Knowledge Graph (KG). In this paper, we present Plumber , the first framework that allows users to manually and automatically create suitable IE pipelines from a community-created pool of tools to perform triple extraction and alignment on unstructured text. Our approach provides an interactive medium to alter the pipelines and perform IE tasks. A short video to show the working of the framework for different use-cases is available online1
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管道工:创建信息提取管道的模块化框架
信息抽取(IE)任务是各个研究领域中经常研究的课题。因此,社区不断地产生多种技术、解决方案和工具来执行这些任务。然而,运行这些工具并将它们集成到现有的基础设施中需要时间、专业知识和资源。这里的一个相关任务是三元组提取和链接,从文本中提取结构化三元组,并将其与现有的知识图(KG)对齐。在本文中,我们介绍了Plumber,这是第一个允许用户从社区创建的工具池中手动和自动创建合适的IE管道的框架,用于对非结构化文本进行三重提取和对齐。我们的方法提供了一个交互的媒介来改变管道和执行IE任务。一个简短的视频展示了框架在不同用例下的工作原理,可以在网上找到1
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