Building structured Knowledge Base for trustable NLP application systems by Resource by Collaborative Construction scheme

Abstract

Wikipedia is an exhaustive resource that contains too much information for any one human to completely absorb. Computers, on the other hand, are able to trawl through information at a rapid pace. However, as Wikipedia is written in such a way that it is clear for people to read, it is not possible for a machine to easily utilise and manipulate this information. Dr Satoshi Sekine is based within the Language Information Access Technology Team at the RIKEN Center for Advanced Intelligent Project, Japan. He is the team leader of a project called SHINRA that is centred around a Resource by Collaborative Contribution (RbCC) scheme and seeks to build a structured knowledge base that combines Wikipedia and an Extended Named Entity (ENE). The RbCC scheme enables the team to work together to construct a resource to advance the field of deep learning. ENE is a hierarchy that is divided into name, time and numerical expressions and the team found that, generally speaking, any question on any specific matter fits within one of these three categories and means that information can potentially be understood by machines engaged in deep learning. The researchers worked to assign appropriate concept class labels and then used references to existing online thesaurus entries and ontology sites to find information that matched the hierarchy. Ultimately, Sekine and the team want to build a structured Wikipedia and to do this categorisation, attribute extraction and attribute value linking will need to be performed.