III: Small: Collaborative Research: Building a Large Multilingual Semantic Network for Text Processing Applications

该项目致力于通过应用专门针对维基百科语料库的语义分析新技术来构建一个大型多语言语义网络。该项目的驱动假设是，维基百科的结构可以有效地用于创建一个高度结构化的世界知识图，其中节点对应于维基百科中描述的实体和概念，而边缘捕获本体关系，如上位关系和部分关系。特别强调的是，利用多语言的信息提供在维基百科，以提高每个语义分析的性能。因此，重要的研究工作旨在开发用于词义消歧、参考解析和本体关系提取的工具，这些工具使用多语言强化和维基百科的一致性结构和重点内容来准确地解决这些任务。另一个研究挑战是有效整合来自多个维基百科文章的固有噪音证据，以提高全球维基百科图中编码的整体知识的可靠性。计算添加到网络中的每一条结构信息的概率置信度值是这种集成中的重要一步，它也意味着为下游应用提供更高的效用。本文提出的高度结构化的语义网络是对现有语义资源的补充，有望对需要大规模世界知识的自然语言处理应用产生广泛的影响。更多信息请访问项目网站：http://lit.csci.unt.edu/index.php/Mu.Se.Net

This project is devoted to building a large multilingual semantic networkthrough the application of novel techniques for semantic analysisspecifically targeted at the Wikipedia corpus. The driving hypothesis ofthe project is that the structure of Wikipedia can be effectively used tocreate a highly structured graph of world knowledge in which nodescorrespond to entities and concepts described in Wikipedia, while edgescapture ontological relations such as hypernymy and meronymy. Specialemphasis is given to exploiting the multilingual information available inWikipedia in order to improve the performance of each semantic analysistool. Significant research effort is therefore aimed at developing toolsfor word sense disambiguation, reference resolution and the extraction ofontological relations that use multilingual reinforcement and theconsistent structure and focused content of Wikipedia to solve these tasksaccurately. An additional research challenge is the effective integrationof inherently noisy evidence from multiple Wikipedia articles in order toincrease the reliability of the overall knowledge encoded in the globalWikipedia graph. Computing probabilistic confidence values for every pieceof structural information added to the network is an important step inthis integration, and it is also meant to provide increased utility fordownstream applications. The proposed highly structured semantic networkcomplements existing semantic resources and is expected to have a broadimpact on a wide range of natural language processing applications in needof large scale world knowledge.For further information, please see the project website:http://lit.csci.unt.edu/index.php/Mu.Se.Net