TALP at eHealth-KD Challenge 2020: Multi-level recurrent and convolutional neural networks for joint classification of key-phrases and relations
Document typeConference report
Rights accessOpen Access
This article describes the model presented by the TALP Team to IberLEF’s eHealth Knowledge Discovery 2020 shared task. The model iterates over the idea of using a single model for simultaneously identify key-phrases and their relationships. Taking into account the new transfer-learning sub-task presented for 2020’s edition of eHealthKD, our model does not rely on any domain-specific knowledge nor handcrafted features. Our model was competitive in all four sub-tasks, ranking in 2nd, 3rd, 4th and 1st position respectively.
CitationMedina, S.; Turmo, J. TALP at eHealth-KD Challenge 2020: Multi-level recurrent and convolutional neural networks for joint classification of key-phrases and relations. A: Iberian Languages Evaluation Forum. "Proceedings of the Iberian Languages Evaluation Forum (IberLEF 2020): co-located with 36th Conference of the Spanish Society for Natural Language Processing (SEPLN 2020): Málaga, Spain, September 23th, 2020". CEUR-WS.org, 2020, p. 85-93. ISBN 1613-0073.