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Tesi triennale Alberto Zerbinati, Simone Mosco. Relatore prof. Andrea Loreggia. @unipd

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SenTag

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License: MIT

SenTag is a light-weight web-based platform for text annotation.

The platform allows multiple users to cooperate in the annotation of a corpus of documents.

The output of the annotation process is an XML file that can be validated against a schema for quality guarantees.

Video Presentation

Demo

  • A demo of SenTag is available here
  • Use the following credential login: username test and password: T3st0n3!

Usage (for local deployment)

  1. Install the dependencies, create the Database and the Admin User, start the Python Backend server

    • Install the dependencies in a new python virtual environment
    python -m venv env
    source env/bin/activate
    pip install -r requirements.txt
    
    • Create the sqlite database
    python manage.py makemigrations
    python manage.py migrate
    
    • Create a superuser
    python manage.py createsuperuser
    
    • Create default Groups (namely Admins, Editors, Annotators) and assign the superuser to them
    python manage.py createdefaultgroups <superuser_name>
    
    • Start the development server:
    python manage.py runserver
    
  2. Open another terminal and start the server for the UI

    cd ui
    yarn install
    yarn serve
    

Now visit http://127.0.0.1:8000 and log in with your credentials for complete access to all functionalities!

Major Dependencies

Paper

SenTag: a Web-based Tool for Semantic Annotation of Textual Documents

  • A. Loreggia, S. Mosco, and A. Zerbinati. "SenTag: a Web-based Tool for Semantic Annotation of Textual Documents" - To appear in Proceedings of the 36th AAAI Conference on Artificial Intelligence 2022 - Demonstrations Program Track

How to cite

@article{sentag2021,
  author = {Loreggia, Andrea and Mosco, Simone and Zerbinati, Alberto},
  journal = {AAAI 2022 - Demonstrations Program},
  booktitle={Proceedings of the 36th AAAI Conference on Artificial Intelligence 2022},
  year={2022},
  title = {SenTag: a Web-based Tool for Semantic Annotation of Textual Documents}
}

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Tesi triennale Alberto Zerbinati, Simone Mosco. Relatore prof. Andrea Loreggia. @unipd

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