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Barbara Starr

Presentation by Vertical Search Works to Semantic Web San Diego - organized by Barbara Starr

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Understanding narrative text is more than simple information extraction on a sentence-by-sentence basis. To comprehend the true meaning of a narrative requires determining the connections between the sentences and the effect of one event on other events. This story understanding process can be greatly enhanced by the use of event descriptor templates that begin with the basic journalistic questions of who, what, when, where, why, and how but that go beyond these simple basics to address more complex relationships: role playing, context, impact, causality, and interests. Previously, representing story narratives as knowledge representations has required intensive manual effort on the part of trained knowledge engineers to correctly encode the contents of stories into a knowledge base (KB). For large volumes of text, this becomes impractical, limiting the usefulness of KB-based systems in question-answering. This paper describes a means of automating the narrative representation process by using event descriptor templates to elicit critical narrative information to be encoded in a knowledge based system.

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Innovative query interfaces to knowledge and database systems must go beyond simply returning the re- quested information. They must be capable of producing intentional answers when a description improves the understanding of an answer [Mot94], producing conditional answers when no one answer matches the conditions of a query, and using ontological information in processing a query. They should be able to call upon stand-alone reasoning modules that are most suitable for a given query. When answering a question involves reasoning beyond a simple lookup, the system must be able to explain the answer to the user.

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ased upon the results of a research project sponsored by the Defense Advance Research Projects Agency (DARP A), called High Performance Knowledge Bases (HPKB). The demonstrated portion of HPKB follows a question- answering paradigm. The integrated architecture developed at Science Applications International Corporation (SAIC), called the HPKB Integrated Knowledge Environment (HIKE) is introduced. Following this, the components involved in the demonstration, which include a natural language understanding system, a first order theorem prover, and a knowledge server are briefly described. The demonstration effectively illustrates the use of both a graphical user interface and a natural language interface to query a first order theorem prover with similar results.

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