We present Web-STAR, an online platform for story understanding built on top of the STAR reasoning engine for STory comprehension through ARgumentation. The platform includes a web-based IDE, integration with the STAR system, and a web service infrastructure to support integration with other systems that rely on story understanding functionality to complete their tasks. The platform also delivers a number of "social" features, including a community repository for public story sharing with a built-in commenting system, and tools for collaborative story editing that can be used for team development projects and for educational purposes.
A relatively new system is Genesis @cite_28 , which deals with both story understanding and storytelling. It models and explores aspects of story understanding using stories drawn from sources ranging from fairy tales to Shakespeare's plays. The system uses the START parser @cite_10 to translate English into a language of relations and events that the system can manipulate. This system is deployed using the Java WebStart mechanism.
@cite_28 @cite_10
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A story summarizer benefits greatly from a reader model because a reader model enables the story summarizer to focus on delivering useful knowledge in minimal time with minimal eort. Such a This paper describes the START Information Server built at the MIT Artificial Intelligence Laboratory. Available on the World Wide Web since December 1993, the START Server provides users with access to multi-media information in response to questions formulated in English. Over the last 3 years, the START Server answered hundreds of thousands of questions from users all over the world. The START Server is built on two foundations: the sentence-level Natural Language processing capability provided by the START Natural Language system and the idea of natural language annotations for multi-media information segments. This paper starts with an overview of sentence-level processing in the START system and then explains how annotating information segments with collections of English sentences makes it possible to use the power of sentence-level natural language processing in the service of multi-media information access. The paper ends with a proposal to annotate the World Wide Web.