Yesterday, we transformed a normal dataset into a graph. Today, let’s do the same thing, but using a text document.
Reuse the article “Python NLP Tutorial: Building A Knowledge Graph using Python and SpaCy” written by Marius Borcan, to do it, but do a few changes:
- Look for an article in your language.
- Describe what’s different in comparison to English language.
- If you have not used the same tools, what have you used instead?
- Think about the entities you are finding and start to create their ontologies in your head.
In my case, instead of using spaCy, I have created my own tagger and tokenizer. This was an “old” project: I did this when I started learning NLP to “live” the whole process.
Other pages you can use to accomplish today’s task are:
- Mining Knowledge Graphs from Text – a tutorial written by Jay Pujara and Sameer Singh.
- Knowledge Graph – A Powerful Data Science Technique to Mine Information from Text (with Python code), written by Prateek Joshi.
During the next days, I will explore data for at least 1 hour per day and post the notebooks, data and models, when they are available, to this repository.
Do you want to connect? It will be a pleasure to discuss Machine Learning with you. Drop me a message on LinkedIn.