A visual timeline authoring tool that extracts temporal information from freeform text
TimeLineCurator was created as part of a Master's thesis at the University of British Columbia, Canada and University of Munich (LMU), Germany.
The running application is hosted on the cloud platform Heroku.
More information and instructions can be found on the project's page
Here's a short video explaining TLC's purpose and functionality.
The project's folder structure:
- nltk_data: Natural Language Toolkit for Python, necessary for splitting freeform text into sentences, tokenizing words etc.
- templates: the HTML templates to which the flask app refers
- ternip: The "Temporal Expression Recognition and Normalisation in Python" library used to find temporal information inside the freeform text (project on GitHub)
- Procfile: declares how to run app dynos on Heroku platform
- app.py: Flask app that contains the Python commands and connects the front-end with the back-end
- requirements.txt: tells Heroku (where the app is hosted) what dependencies we need