AbstractInformation extraction is the process of converting unstructured text into a structured data base containing selected information from the text. It is an essential step in making the information content of the text usable for further processing. In this paper, we describe how information extraction has changed over the past 25 years, moving from hand-coded rules to neural networks, with a few stops on the way. We connect these changes to research advances in NLP and to the evaluations organized by the US Government.
Model-based Hyperparameter Optimization of Convolutional Neural Networks for Information Extraction from Cancer Pathology Reports on HPC