Entity Relationship Extraction Method Based on Dependency Syntax Analysis and Rules

Abstract

With the advent of the Internet era, the content of network information has largely increased, hence information extraction has became significant. As an important sub-task of information extraction, entity relationship extraction is also paid more and more attention. Most current entity relationship extraction methods not only require manual annotation, but the quality of annotation also cannot be guaranteed, besides the evaluation criteria has not been unified yet. Therefore, this paper proposes an entity relationship extraction method based on the combination of dependency syntax analysis and rules. The method does not need to annotate the input text manually, dependency parsing is used to determine the sentence components and the relationships among them. Meanwhile, a semantic triple representing entity relations is formed and output by combining rules. The experiment results shows that the method proposed in this paper has a good effect and saves labor cost. The average accuracy in corpus reaches 63.04%, the average output time of triples is shortened as well.