ConceptNet — a practical commonsense reasoning tool-kit

Computers are quite good now at dealing with specifics: you can ask Siri "how far is it to the moon?" and it will reply "about 376,000 kilometers," but computers still struggle with common sense knowledge. For example, if someone says, "I want some chips right now," humans will often interpret "chips" as meaning potato chips. But "chips" may easily confuse a computer system. Are we talking about potato chips? Computer chips? Wood chips? Poker Chips? To solve this type of problem researchers at MIT's Media Lab have developed ConceptNet, which they describe as: " a freely available common sense knowledge base and natural-language-processing tool-kit which supports many practical textual-reasoning tasks over real-world documents including topic-gisting, analogy-making, and other context oriented inferences. The knowledge base is a semantic network presently consisting of over 1.6 million assertions of common sense knowledge encompassing the spatial, physical, social, temporal, and psychological aspects of everyday life. ConceptNet is generated automatically from the 700 000 sentences of the Open Mind Common Sense Project — a World Wide Web based collaboration with over 14,000 authors."
   ConceptNet recently took an intelligence test and scored about the same as a 4 year old child, but since then its knowledge-base has increased ten fold. Are computers that can really understand what we say almost with us? ConceptNet is an open source project, with a Python implementation and a API that anyone can use to add computational common sense to their own project.