Man bites dog: looking for interesting inconsistencies in structured news reports

Much useful information in news reports is often that which is surprising or unexpected. In other words, we harbour many expectations about the world, and when any of these expectation are violated (i.e. made inconsistent) by news, we have a strong indicator of some information that is interesting for us. In this paper we present a framework for identifying interesting information in news reports by finding interesting inconsistencies. An implemented system based on this framework (1) accepts structured news reports as inputs, (2) translates each report to a logical literal, (3) identifies the story of which the report is a part, (4) looks for inconsistencies between the report, the background knowledge, and a set of expectations, (5) classifies and evaluates those inconsistencies, and (6) outputs news reports of interest to the user together with associated explanations of why they are interesting.