Parallel memory-based parsing on SNAP

The paper presents a parallel natural language processing system implemented on a marker-passing parallel AI computer, Semantic Network Array Processor (SNAP). The 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 linguistic patterns that reflect a sentence interpretation. This is achieved via propagating markers over the distributed network. The authors 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 performance results obtained