Verb Based Conceptual Common Sense Extraction

Ji Youlang, Yu Yang, Z. Hongying, Zhu Jun, Gu Jingjing, Hua Lingya
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引用次数: 1

Abstract

The knowledge in the knowledge bases such as Freebase, Knowledge Vault and so on are all facts which record the relationships between two entities. It may lead to following two problems. First, this form of knowledge limits the scale of the existing knowledge bases. When extracting new facts, no good patterns with a good ability of summarization can be used. Second, when applied in some real tasks, the knowledge may always suffer the problem of data sparsity. To solve these two problems, in this paper, we define the problem of extracting common senses in a concept level. We evaluate our solutions on Google N-Grams data set, and the results shows a great improvement.
基于动词的概念常识提取
Freebase、knowledge Vault等知识库中的知识都是记录两个实体之间关系的事实。这可能会导致以下两个问题。首先,这种形式的知识限制了现有知识库的规模。在提取新的事实时,不能使用具有良好总结能力的好的模式。其次,当应用于实际任务时,这些知识可能总是存在数据稀疏性的问题。为了解决这两个问题,本文在概念层面定义了常识抽取问题。我们在Google N-Grams数据集上对我们的解决方案进行了评估,结果显示出了很大的改进。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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