Digger: NLP Enhanced Search

Digger has a table set up here at AAAI 2007 in Vancouver. I've not yet had a look at their beta (a random encounter in an elevator may lead to getting an invite) but they do have a few examples queries available on their website (the demo at the conference allows you to enter any query).

They do a couple of nice things in their demo interface. Firstly, they give you a break down of the interpretation they have given to your query. Secondly, in the snippets they return, the provide extra information for each of the terms that were used in the match (which may not be literally present in the query).

Below shows the query information for the query 'moving a chess horse.'

While Digger is going for a similar level of semantic resolution as Powerset, it is applying its technology to the query and the snippets from the result set - not computing an entire semantic index in the back end.

I'm interested in the general strategy of exposing the results of analysis in the manner that Digger does. It allows for direct comparisons with other enterprises adopting the same approach (here is Hakia's interpretation of the same input). That being said, it also reminds me of the way in which Ask Jeeves (the original iteration) reported results. It is impressive when it is right, but when the reporting of the interpretation allows the user to edit mistakes - even though that may help the user at that instant - the perception is of a hedged interface.