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FAUST: Flexible Acquisition and Understanding System for Text
SRI is developing an automated reading system that makes the information in textbooks accessible to a range of formal reasoning systems.
SRI's Machine Reading Program is creating an automated reading system that makes the information in natural language texts accessible to a range of formal reasoning systems.
In the Flexible Acquisition and Understanding System for Text (FAUST) project, SRI proposes architecture based on statistical joint inference over probabilistic relational models. Supporting the simultaneous consideration of random variables enables leveraging all mutually constraining information and the integration of information across sentences and texts. This joint inference engine will integrate information from more specialized inference modules — in particular, an ensemble of natural language modules. Such integration requires the coordination or alignment of representations from multiple levels of analysis and multiple texts.
SRI is continually improving these alignments using machine learning techniques. This approach builds on significant recent advances in probabilistic representation and joint inference. It will enable the system to consider the widest range of both linguistic and extra-linguistic evidence, using the same mechanisms that are used for the integration of linguistic information across levels.