eHealth-KD Challenge 2021

This project is the final submission for the eHealth-KD Challenge by the UH-MMM team at IberLEF 2021. The project focuses on Named Entity Recognition (NER) and Relation Extraction (RE) using machine learning models.

Overview

Two main subtasks for knowledge discovery were defined: entity recognition and relationship extraction.
The evaluation of the task is divided into three scenarios: one corresponding to the detection of entities, one corresponding to the detection of relations between such pair of entities, and the third one corresponding to the extraction of both entities and relationships.
For both subtasks, our proposal makes use of BiLSTM as contextual encoders and Dense layers as the tag decoder architecture of the model.
In the challenge, the system ranked fifth in the main scenario, fourth in the scenario evaluating the first task, and fifth in the last scenario.
The score obtained in the relationship extraction task shows that the proposed approach needs to be further explored.