eHealthKD-competition

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

Project Structure

• 2021: Contains the data available for the competition, including training, development, and test datasets.
• scripts: Contains the source code for the implemented models.
  • ner_clsf.py: NER model implementation.
  • re_clsf.py: RE model implementation.
  • classifier.py: Wraps the NER and RE models for testing in various scenarios.

Setup Instructions

To use the system:

1. Download the FastText Spanish Medical Embeddings from Zenodo.
2. Unzip the embeddings file "Scielo+Wiki SkipGram Uncased" into the scripts directory.

License

This project is licensed under the MIT License.

Citation

If you use this code, please refer to the associated paper for more details.

For further information, refer to the documentation paper.