Graph Convolutional Networks for Named Entity Recognition
Alberto Cetoli, Stefano Bragaglia, Andrew D. O’Harney, Marc Sloan · arXiv (Cornell University) · 2017
In this paper we investigate the role of the dependency tree in a named entity recognizer upon using a set of GCN. We perform a comparison among different NER architectures and show that the grammar of a sentence positively influences the results. Experiments on the ontonotes dataset demonstrate consistent performance improvements, without requiring heavy feature engineering nor additional language-specific knowledge.