Jason Alan Fries

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We submitted two systems to the SemEval-2016 Task 12: Clinical TempEval challenge, participating in Phase 1, where we identified text spans of time and event expressions in clinical notes and Phase 2, where we predicted a relation between an event and its parent document creation time. For temporal entity extraction, we find that a joint inference-based(More)
We describe a vision and an initial prototype system for extracting structured data from unstructured or dark input sources–such as text, embedded tables, images, and diagrams–called Snorkel 1 , in which users write traditional extraction scripts which are automatically enhanced by machine learning techniques. The key technical idea is to view the user's(More)
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