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Over 50 million scholarly articles have been published: they constitute aunique repository of knowledge. In particular, one may infer from themrelations between scientific concepts, such as synonyms and hyponyms.Artificial neural networks have been recently explored for relation extraction.In this work, we continue this line of work and present a system based on aconvolutional neural network to extract relations. Our model ranked first inthe SemEval-2017 task 10 (ScienceIE) for relation extraction in scientificarticles (subtask C).

MIT at SemEval-2017 Task 10: Relation Extraction with Convolutional Neural Networks