Papers › Graph Convolutional Networks for Named Entity Recognition
Graph Convolutional Networks for Named Entity Recognition
A. Cetoli, S. Bragaglia, A. D. O'Harney, M. Sloan
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.
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