A Entity Relation Extraction Method Based on Wikipedia and Pattern Clustering

This paper proposes a method to extract Chinese entity relations of high accuracy from open text based on Wikipedia and pattern clustering.We get relation instances by a mapping from HowNet to Wikipedia and via the structural characteristics of Wikipedia.Based on these,the method solves the entity recognition and generates significant sentence instances.Furthermore,significance assumption and keyword assumption are proposed to support classification and hierarchy clustering algorithm for pattern reliability.The results show that the method achieves a good performance with high-quality seeds and patterns.