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Abstract:
The long term goal of the TRAINS project is to develop an intelligent planning assistant that is conversationally proficient in natural language. The TRAINS system helps a user construct and monitor plans about a railroad freight system; their interaction takes place in natural language. The representational needs of a system like TRAINS include representing lexical meaning, dealing with the problem of ambiguity, make use of information about context, and finding a connection between the content of the current utterance and the plan being jointly developed by system and user. The goal of the paper is to describe how TRAINS-93, the latest prototype of TRAINS, deals with these issues.