API for NER system based on a BiLSTM-CNN-CRF with BERT

This repository provides an API access to the models trained with a (BiLSTM-CNN-CRF and BERT)[https://github.com/EMBEDDIA/bert-bilstm-cnn-crf-ner].

Flask REST API skeleton with dockerized Flask + flask_restx, Gunicorn, Nginx, Celery, Flower and Redis

This repository is based on flask-rest-docker which in turn extends flask-on-docker with Celery, Redis and Flask_restx to provide a skeleton for building dockerized Flask RESTful APIs. This version includes a container (ner-service) which make use of miniconda to facilitate the import of requirements.

Main Requirements

docker
docker-compose

Selecting which models to load

In the path services/ner-service there is a configuration file (config.json). Currently, only one model is being loaded as indicated with "loadLanguages": ["hr"]. If more languages want to be loaded, it is necessary to add them to the list. However, if all the models want to be loaded, you can remove that line from the configuration file and the program will load all the available models.

Development

The following command

$ docker-compose build

will build the images and run the containers.

The following command

$ docker-compose up

If you go to http://0.0.0.0:5000 you will see a web interface where you can check and test your REST API. Flower monitor for Celery is running on http://0.0.0.0:5555. Note that the web folder is mounted into the container and the Flask development server reloads your code automatically so any changes will be visible immediately.

License

This work has been attributed an MIT License and makes use of portions of code from the following repositories:

flask-rest-docker: MIT License
flask-on-docker: MIT License

How to cite?

@inproceedings{moreno-etal-2019-tlr,
    title = "{TLR} at {BSNLP}2019: A Multilingual Named Entity Recognition System",
    author = "Moreno, Jose G.  and
      Linhares Pontes, Elvys  and
      Coustaty, Mickael  and
      Doucet, Antoine",
    booktitle = "Proceedings of the 7th Workshop on Balto-Slavic Natural Language Processing",
    month = aug,
    year = "2019",
    address = "Florence, Italy",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/W19-3711",
    doi = "10.18653/v1/W19-3711",
    pages = "83--88"
}

Parent project

This work is is result of the European Union H2020 Project Embeddia. Embeddia is a project that creates NLP tools that focuses on European under-represented languages and that has for objective to improve the accessibility of these tools to the general public and to media enterprises. Visit Embeddia's Github to discover more NLP tools and models created within this project.

EMBEDDIA / ULR_NER_REST