A Self-learning Template Approach for Recognizing Named Entities from Web Text
Qian Liu, Bingyang Liu, Dayong Wu, Yue Liu, Xueqi Cheng · International Joint Conference on Natural Language Processing · 2013
Recognizing Chinese Named entities from the Web is challenging, due to the lack of labeled data and differences between Chinese and English. We propose a semisupervised approach which leverages seed entities and the large unlabeled data to learn templates. Some high-quality templates are generated iteratively to extract new named entities based on the model of quality metrics. Experimental results show that our approach significantly outperforms the baseline method and it is robust against the changes of the Web.