Generating natural language summaries from multiple online sources

We present a methodology for summarization of news about current events in the form of brief-ings that include appropriate background (historical) information. The system that we developed, SUMMONS, uses the output of systems developed for the DARPA Message Understanding Con-ferences to generate summaries of multiple documents on the same or related events, presenting similarities and differences, contradictions, and generalizations among sources of information. We describe the various components ofthe system, showing how information from multiple arti-cles is combined, organized into a paragraph, and finally, realized as English sentences. A feature of our work is the extraction of descriptions of entities such as people and places for reuse to enhance abriefing. 1