A Distributed Architecture for Interactive Parse Annotation

In this paper we describe a modular system ar- chitecture for distributed parse annotation us- ing interactive correction. This involves inter- actively adding constraints to an existing parse until the returned parse is correct. Using a mixed initiative approach, human annotators in- teract live with distributed ccg parser servers through an annotation gui. The examples pre- sented to each annotator are selected by an ac- tive learning framework to maximise the value of the annotated corpus for machine learners. We report on an initial implementation based on a distributed workflow architecture.