Distant Supervision for Relation Extraction via Piecewise Convolutional Neural Networks

Authors: Daojian Zeng, Kang Liu, Yubo Chen, Jun Zhao - Conference on Empirical Methods in Natural Language Processing, EMNLP 2015 cited by 1,215

Two problems arise when using distant supervision for relation extraction. First, in this method, an already existing knowledge base is heuristically aligned to texts, and the alignment results are treated as labeled data. However, the heuristic alignment can fail, resulting in wrong label problem. In addition, in previous approaches, statistical models have typically been applied to ad hoc features. The noise that originates from the feature extraction process can cause poor performance.