Semantic interpretation and the resolution of ambiguity
Semantic interpretation and the resolution of ambiguity
The teachable language comprehender: a simulation program and theory of language
Communications of the ACM
Integrating Marker Passing and Problem Solving: A Spreading Activation Approach to Improved Choice in Planning
Inside Case-Based Reasoning
SNAP: A Market-Propagation Architecture for Knowledge Processing
IEEE Transactions on Parallel and Distributed Systems
The SNAP-1 Parallel AI Prototype
IEEE Transactions on Parallel and Distributed Systems
USC: description of the SNAP system used for MUC-4
MUC4 '92 Proceedings of the 4th conference on Message understanding
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This paper presents a parallel natural language processing system implemented on a marker-passing parallel AI computer, the Semantic Network Array Processor (SNAP). Our system uses a memory-based parsing approach in which parsing is viewed as a memory search process. Linguistic information is stored as phrasal patterns in a semantic network knowledge base distributed over the memory of the parallel computer. Parsing is performed by recognizing and linking phrasal patterns that reflect a sentence interpretation. This is achieved by propagating markers over the distributed network. We have developed a system capable of processing newswire articles from a particular domain. The paper presents the structure of the system, the memory-based parsing method used, and the performance results obtained.