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ConceptNet aims to give computers access to common-sense knowledge, the kind of information that ordinary people know but usually leave unstated. The data in ConceptNet is being collected from ordinary people who contributed it on sites like Open Mind Common Sense. ConceptNet represents this data in the form of a semantic network, and makes it available to be used in natural language processing and intelligent user interfaces.

ConceptNet is a semantic network containing lots of things computers should know about the world, especially when understanding text written by people. It is built from nodes representing concepts, in the form of words or short phrases of natural language, and labeled relationships between them. These are the kinds of things computers need to know to search for information better, answer questions, and understand people's goals. ConceptNet contains everyday basic knowledge:

Overview When people communicate, they rely on a large body of shared common sense knowledge in order to understand each other. Many barriers we face today in artificial intelligence and user interface design are due to the fact that computers do not share this knowledge. To improve computers' understanding of the world that people live in and talk about, we need to provide them with usable knowledge about the basic relationships between things that nearly every person knows. In 1999, we began a project at the MIT Media Lab to collect common sense from volunteers on the internet. Ten years later our project has expanded to encompass many different areas, languages, and problems. Currently, the English site has over a million sentences from over 15,000 contributors.