I ran a named entity extractor on the following URL http://computationalimagination.com/article_empirical_question.php http://computationalimagination.com/arti

I ran a named entity extractor on the following URL http://computationalimagination.com/article_empirical_question.php http://computationalimagination.com/article_empirical_questi... The opening of this article has several entities that are easy for a human to parse out and the Summarizer did OK but still well behind a human. "That's an empirical question! I was walking down Church Street toward Coffman Union on the U of Minnesota campus, shooting the breeze and arguing with a fellow grad student when I first heard those words from Bill. Bill [William D. Wells] had recently been lured out of semi-retirement from the advertising agency DDB Needham and back into academia." Intellexer missed the common U as a sign for University particularly when followed by "of" and either another capital letter such as "U of M" or as in the case above "U of Minnesota" the name of a place. It did capture Coffman Union, Minnesota and Church Street as locations. Which is technically correct but because it didn't recognized U of Minnesota campus as a broader location it cannot place Coffman Union and Church Street as sub locations within a larger entity. The "Clusterizer" identified some reasonable clusters, really more like a list of important key words. The "Summarizer" which seems to just try to find the best summary sentences from within the text and present them was a very mixed bag. Of the 10 sentences it picked 6 were good and 4 were clear misses in terms of picking out good summary sentences. Overall not bad. But also not surprisingly good. For comparison - I used this same article as a test of the IBM Watson NLP API for entity extraction a few months ago and Intellexer did a little bit better.