Relation Extraction from Wikipedia Leveraging Intrinsic Patterns
Enormous efforts of human volunteers have made Wikipedia become a treasure of textual knowledge. Relation extraction that aims at extracting structured knowledge in the unstructured texts in Wikipedia is an appealing but quite challenging problem because it's hard for machines to understand plain texts. Existing methods are not effective enough because they understand relation types in textual level without exploiting knowledge behind plain texts. In this paper, we propose a novel framework called Athena leveraging Intrinsic Patterns which are patterns that can understand relation types in semantic level to solve this problem. Extensive experiments show that Athena significantly outperforms existing methods.