NL2KB: Resolving Vocabulary Gap between Natural Language and Knowledge Base in Knowledge Base Construction and Retrieval
Sheng-Lun Wei, Yen-Pin Chiu, Hen-Hsen Huang, Hsin-Hsi Chen
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Words to express relations in natural language (NL) statements may be different from those to represent properties in knowledge bases (KB). The vocabulary gap becomes barriers for knowledge base construction and retrieval. With the demo system called NL2KB in this paper, users can browse which properties in KB side may be mapped to for a given relational pattern in NL side. Besides, they can retrieve the sets of relational patterns in NL side for a given property in KB side. We describe how the mapping is established in detail. Although the mined patterns are used for Chinese knowledge base applications, the methodology can be extended to other languages.