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Brian Harrington

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AAAI Conference 2007 Conference Paper

ASKNet: Automated Semantic Knowledge Network

Brian Harrington

The ASKNet system is an attempt to automatically generate large scale semantic knowledge networks from natural language text. State-of-the-art language processing tools, including parsers and semantic analysers, are used to turn input sentences into fragments of semantic network. These network fragments are combined using spreading activation-based algorithms which utilise both lexical and semantic information. The emphasis of the system is on wide-coverage and speed of construction. In this paper we show how a network consisting of over 1. 5 million nodes and 3. 5 million edges, more than twice as large as any network currently available, can be created in less than 3 days. We believe that the methods proposed here will enable the construction of semantic networks on a scale never seen before, and in doing so reduce the knowledge acquisition bottleneck for AI.

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AAAI Conference 2007 Short Paper

ASKNet: Automatically Generating Semantic Knowledge Networks

Brian Harrington

The ASKNet project uses a combination of NLP tools and spreading activation to transform natural language text into semantic knowledge networks. Network fragments are generated from input sentences using a parser and semantic analyser, then these fragments are combined using spreading activation based algorithms. The ultimate goal of the project is to create a semantic resource on a scale that has never before been possible. We have already managed to create networks more than twice as large as any comparable resource(1. 5 million nodes, 3. 5 million edges) in less than 3 days. This report provides a summary of the project and its current state of development.

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