Using your Jupyter notebook for a quick demo of NER and Microsoft Text Analytics API

I recently came across how to use an Ipython widget to put forth simple demo of powerful capabilities in Natural Language Processing. This can be things like simple API calls, NLTK processing functions, etc.

I shall demonstrate a simple demo of how to accept a text entry from a user and call the Microsoft’s Text Analytics API to detect key Phrases. We can also invoke the default NLTK Named Entity Recognition tagger similarly.

A GIF showing how a simple widget can be used to identify entities in a given piece of text

Calling the Azure Text Analytics API

A simple demo of calling the text analytics API can be accomplished in seconds, thanks to IPython widgets.

Showcasing the simple use of a Ipython widget to call the text analytics API

Feel free to play around with other API calls that you can make with text analytics API or other Microsoft cognitive services.

The code snippet can be found at this repository: https://github.com/kishan19/Kishans-Data-Science-Blog/tree/master/NER_Demo%2BText_Analytics

References:

1. https://docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/quickstarts/python

2. https://stackoverflow.com/questions/31836058/nltk-named-entity-recognition-to-a-python-list

3. https://ipywidgets.readthedocs.io/en/stable/examples/Widget%20List.html#Text