Coin_flipper at eHealth-KD challenge 2019: voting LSTMs for key phrases and semantic relation identification applied to spanish eHealth texts
Document typeConference report
Rights accessOpen Access
This paper describes our approach presented for the eHealthKD 2019 challenge. Our participation was aimed at testing how far we could go using generic tools for Text-Processing but, at the same time, using common optimization techniques in the field of Data Mining. The architecture proposed for both tasks of the challenge is a standard stacked 2-layer bi-LSTM. The main particularities of our approach are: (a) The use of a surrogate function of F1 as loss function to close the gap between the minimization function and the evaluation metric, and (b) The generation of an ensemble of models for generating predictions by majority vote. Our system ranked second with an F1 score of 62.18% in the main task by a narrow margin with the winner that scored 63.94%
CitationCatalà Roig, N.; Martin, M. Coin_flipper at eHealth-KD challenge 2019: voting LSTMs for key phrases and semantic relation identification applied to spanish eHealth texts. A: Iberian Languages Evaluation Forum. "Proceedings of the Iberian Languages Evaluation Forum (IberLEF 2019): co-located with 35th Conference of the Spanish Society for Natural Language Processing (SEPLN 2019): Bilbao, Spain, September 24th, 2019". CEUR-WS.org, 2019, p. 17-25.