This position paper argues for an interactive approach to text understanding. The proposed model extends an existing semantics-based text authoring system by using the input text as a source of information to assist the user in re-authoring its content. The approach permits a reliable deep semantic analysis by combining automatic information extraction with a minimal amount of human intervention. the various authoring choices; in each menu the choices are then ranked according to their likelihood, allowing a speedier selection by the author; when the likelihood of a choice exceeds a certain threshold, this choice is performed automatically by.
