Established: December 19, 2001


MindNet is a knowledge representation project that uses our broad-coverage parser to build semantic networks from dictionaries, encyclopedias, and free text. MindNets are produced by a fully automatic process that takes the input text, sentence-breaks it, parses each sentence to build a semantic dependency graph (Logical Form), aggregates these individual graphs into a single large graph, and then assigns probabilistic weights to subgraphs based on their frequency in the corpus as a whole. The project also encompasses a number of mechanisms for searching, sorting, and measuring the similarity of paths in a MindNet. We believe that automatic procedures such as MindNets provide the only credible prospect for acquiring world knowledge on the scale needed to support common-sense reasoning.

Online Browsing

MindNet Browsing Now Available! If you are interested in more detailed information about MindNets, a small number of sample MindNets have been made available for online browsing at the mnex project homepage.



Portrait of Arul Menezes

Arul Menezes

Partner Research Manager

Portrait of Bill Dolan

Bill Dolan

Partner Research Manager

Portrait of Chris Brockett

Chris Brockett

Principal Researcher