Improving Summaries by Revising Them

This paper describes a program which revises a draft text by aggregating together descriptions of discourse entities, in addition to deleting extraneous information. In contrast to knowledge-rich sentence aggregation approaches explored in the past, this approach exploits statistical parsing and robust coreference detection. In an evaluation involving revision of topic-related summaries using informativeness measures from the TIPSTER SUMMAC evaluation, the results show gains in informativeness without compromising readability.