With the considerable growth of linked data, researchers have focused on how to increase the availability of semantic web technologies to provide practical usages for real life systems. Question answering systems are an example of real-life systems that communicate directly with end users, understand user intention and generate answers. End users do not care about the structural query language or the vocabulary of the knowledge base where the point of a problem arises. In this study, a question answering framework that converts Turkish natural language input into SPARQL queries in the geographical domain is proposed. Additionally, a novel Turkish ontology, which covers a 10th grade geography lesson named Spatial Synthesis Turkey, has been developed to be used as a linked data provider. Moreover, a gap in the literature on Turkish question answering systems, which utilizes linked data in the geographical domain, is addressed. A hybrid system architecture that combines natural language processing techniques with linked data technologies to generate answers is also proposed. Further related research areas are suggested.
翻译:随着连结数据的大量增加,研究人员集中研究如何增加语义网络技术的可用性,以便为实际生活系统提供实用的用途。回答问题系统是实际生活系统的一个实例,这些系统直接与终端用户沟通,了解用户的意图并产生答案。终端用户不关心结构查询语言或知识库词汇,因为出现问题的地方会出现问题。在这项研究中,提出了将土耳其的自然语言输入转换为地理领域的SPARQL查询的回答问题框架。此外,还开发了一个土耳其新颖的文理学,其中包括10年级地理学课程,称为“空间合成土耳其”,作为链接的数据提供者使用。此外,还解决了土耳其问题解答系统文献中的空白,该系统利用地理领域的链接数据。还提出了将自然语言处理技术与链接的数据技术相结合以产生答案的混合系统结构。还提出了进一步的相关研究领域。