"It works!" Of all the words in the English language, those two have to be the sweetest. Especially when heard at regular intervals. Here's one more demo slide of the grammar parser at work.

1. One of the many advantages of tagging text with Parts of Speech (PoS)
tokens is that it makes the content much more pliable for querying.
The assumption, and the finding, was that when it comes to text analysis,
grammar knows best. And that grammar and graph work very well together
to give you more insights into the data.
In this instance, we analysed Nokia’s three months of Twitter|FB
conversation data, and graphed them across seven brand parameters, after
ascribing “tone” to the content. (Instead of sentiment, we go by tone.)
By plotting Frequency (high-low scale), with Tone (positive-negative scale),
we publish a “voiceprint” of the brand's conversation.
Take a look at the full report at http://metaphic.in/nokia/somaReport.php
What is the shape and tone of your brand’s voice?
Now, we can show you by extracting a "voiceprint" from text data.
Metaphic
Takes a minute or so. Lacks ux/ui so just click on stuff. Welcome feedback manian@conversation.co.in
Grammatically Different.